Relevant bibliographies by topics / Mechanical optimizations

Contents

  1. Journal articles
  2. Dissertations / Theses
  3. Books
  4. Book chapters
  5. Conference papers
  6. Reports

Academic literature on the topic 'Mechanical optimizations'

Author: Grafiati
Published: 9 June 2023

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Journal articles on the topic "Mechanical optimizations"

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Vlahopoulos, N., and C. G. Hart. "A Multidisciplinary Design Optimization Approach to Relating Affordability and Performance in a Conceptual Submarine Design." Journal of Ship Production and Design 26, no. 04 (November 1, 2010): 273–89. http://dx.doi.org/10.5957/jspd.2010.26.4.273.

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A multidisciplinary design optimization (MDO) framework is used for a conceptual submarine design study. Four discipline-level performances—internal deck area, powering, maneuvering, and structural analysis—are optimized simultaneously. The four discipline-level optimizations are driven by a system level optimization that minimizes the manufacturing cost while at the same time coordinates the exchange of information and the interaction among the discipline-level optimizations. Thus, the interaction among individual optimizations is captured along with the impact of the physical characteristics of the design on the manufacturing cost. A geometric model for the internal deck area of a submarine is created, and resistance, structural design, and maneuvering models are adapted from theoretical information available in the literature. These models are employed as simulation drivers in the discipline-level optimizations. Commercial cost-estimating software is leveraged to create a sophisticated, automated affordability model for the fabrication of a submarine pressure hull at the system level. First, each one of the four discipline optimizations and also the cost-related top level optimization are performed independently. As expected, five different design configurations result, one from each analysis. These results represent the "best" solution from each individual discipline optimization, and they are used as reference for comparison with the MDO solution. The deck area, resistance, structural, maneuvering, and affordability models are then synthesized into a multidisciplinary optimization statement reflecting a conceptual submarine design problem. The results from this coordinated MDO capture the interaction among disciplines and demonstrate the value that the MDO system offers in consolidating the results to a single design that improves the discipline-level objective functions while at the same time produces the highest possible improvement at the system level.
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Mo, Yu Zhen, and Jia Chu Xu. "Studies on Mechanical Properties and Optimization Model of PI/SiO2 Nanocomposite Based on Materials Studio." Advanced Materials Research 1049-1050 (October 2014): 54–57. http://dx.doi.org/10.4028/www.scientific.net/amr.1049-1050.54.

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The unit cell models of PI/SiO2 nanocomposite was built by Materials Studio. The stiffness matrix and mechanical properties parameters such as Young modulus, shear modulus, bulk modulus and Poisson ratio of the unit cells were achieved after molecular dynamic (MD) optimizations and calculations. The influence factors on the mechanical properties of nanocomposite were analyzed. Finally, the optimization model was achieved.
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Xu, Haoran, Lingen Chen, Yanlin Ge, and Huijun Feng. "Four-Objective Optimization of an Irreversible Stirling Heat Engine with Linear Phenomenological Heat-Transfer Law." Entropy 24, no. 10 (October 19, 2022): 1491. http://dx.doi.org/10.3390/e24101491.

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This paper combines the mechanical efficiency theory and finite time thermodynamic theory to perform optimization on an irreversible Stirling heat-engine cycle, in which heat transfer between working fluid and heat reservoir obeys linear phenomenological heat-transfer law. There are mechanical losses, as well as heat leakage, thermal resistance, and regeneration loss. We treated temperature ratio x of working fluid and volume compression ratio λ as optimization variables, and used the NSGA-II algorithm to carry out multi-objective optimization on four optimization objectives, namely, dimensionless shaft power output P¯s, braking thermal efficiency ηs, dimensionless efficient power E¯p and dimensionless power density P¯d. The optimal solutions of four-, three-, two-, and single-objective optimizations are reached by selecting the minimum deviation indexes D with the three decision-making strategies, namely, TOPSIS, LINMAP, and Shannon Entropy. The optimization results show that the D reached by TOPSIS and LINMAP strategies are both 0.1683 and better than the Shannon Entropy strategy for four-objective optimization, while the Ds reached for single-objective optimizations at maximum P¯s, ηs, E¯p, and P¯d conditions are 0.1978, 0.8624, 0.3319, and 0.3032, which are all bigger than 0.1683. This indicates that multi-objective optimization results are better when choosing appropriate decision-making strategies.
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Lee, Youngmyung, Yong-Ha Han, Sang-ok Park, and Gyung-Jin Park. "Vehicle crash optimization considering a roof crush test and a side impact test." Proceedings of the Institution of Mechanical Engineers, Part D: Journal of Automobile Engineering 233, no. 10 (September 5, 2018): 2455–66. http://dx.doi.org/10.1177/0954407018794259.

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The vehicle performances for the side impact test and the roof crush test are dependent on the side structure design of a vehicle. Crash optimization can be employed to enhance the performances. A meta-model-based structural optimization technique is generally utilized in the optimization process since the technique is simple to use. However, the meta-model-based optimization is not suitable for problems with many design variables such as topology and topometry optimizations. A crash optimization methodology is proposed to consider both the side impact test and the roof crush test. The equivalent static loads method is adopted for the side impact test and the enforced displacement method is adopted for the roof crush test, and the two methods are integrated. A design formulation is defined. The survival distance from the side impact test and the roof strength for the roof crush test are used for the design constraints. Crash optimization is performed for a practical large-scale structure. For conceptual design, reinforcement of the B-pillar is determined by using topometry optimization, and size and shape optimizations are employed for a detailed design to satisfy the design constraints while the mass is reduced.
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Sun, S., Z. Fan, Y. Wang, and J. Haliburton. "Organic solar cell optimizations." Journal of Materials Science 40, no. 6 (March 2005): 1429–43. http://dx.doi.org/10.1007/s10853-005-0579-x.

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Du, Yun Peng, Guo Liang Hu, and Fei Dong. "Study on Structural Design and Optimization Analysis for 2V80 Engine Piston Based on Finite Element Analysis." Advanced Materials Research 753-755 (August 2013): 1188–91. http://dx.doi.org/10.4028/www.scientific.net/amr.753-755.1188.

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According to the experiment of engine bench test and piston's temperature field, the thermal boundary conditions and the mechanical conditions of piston are obtained. Under the condition of mechanical load and thermal load playing, the stress and strain of original engine is simulated and analyzed. Stress concentration and weak structure of original engine is found. The parameter of piston structure is optimized and the optimizations are put forward and analyzed to verify the optimizations' effectiveness. These provide a reference for the digital modeling and numerical analysis to solver engineering problems.
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Xiong, Zhe, Xiao-Hui Li, Jing-Chang Liang, and Li-Juan Li. "A Multi-Objective Hybrid Algorithm for Optimization of Grid Structures." International Journal of Applied Mechanics 10, no. 01 (January 2018): 1850009. http://dx.doi.org/10.1142/s1758825118500096.

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In this study, a novel multi-objective hybrid algorithm (MHGH, multi-objective HPSO-GA hybrid algorithm) is developed by crossing the heuristic particle swarm optimization (HPSO) algorithm with a genetic algorithm (GA) based on the concept of Pareto optimality. To demonstrate the effectiveness of the MHGH, the optimizations of four unconstrained mathematical functions and four constrained truss structural problems are tested and compared to the results using several other classic algorithms. The results show that the MHGH improves the convergence rate and precision of the particle swarm optimization (PSO) and increases its robustness.
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Wan, Zhi-Qiang, Xiao-Zhe Wang, and Chao Yang. "Integrated aerodynamics/structure/stability optimization of large aircraft in conceptual design." Proceedings of the Institution of Mechanical Engineers, Part G: Journal of Aerospace Engineering 232, no. 4 (January 11, 2017): 745–56. http://dx.doi.org/10.1177/0954410016687143.

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The multidisciplinary design optimization is suitable for modern large aircraft, and it has the potential in conceptual phase of aircraft design especially. An integrated optimization method considering the disciplines of aerodynamics, structure and stability for large aircraft design in conceptual phase is presented. The objective is the minimum stiffness of a beam-frame wing structure subject to aeroelasticity, aerodynamics, and stability constraints. The aeroelastic responses are computed by commercial software MSC. Nastran, and the cruise stability is evaluated by the linear small-disturbance equations. A viscous-inviscid iteration method, which is composed of a computational fluid dynamics tool solving the Euler equations and a viscous correction method, is used for computing the flow over the model. The method ensures effective and rapid computation. In this paper, a complete aircraft model is optimized, and all the responses are computed in the trim condition with a fixed maximum takeoff weight. Genetic algorithm is utilized for global optimizations, and the optimal jig shape, the elastic axis positions and the stiffness distribution can be attained adequately. The results show that the method has a value of application in engineering optimizations. For the satisfaction of the total drag and stability constraints, the structure weight usually needs a price to pay. The integrated optimization captures the tradeoff between aerodynamics, structure and stability, and the repeated design can be avoided.
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López, Luis Fernando de Mingo, Francisco Serradilla García, José Eugenio Naranjo Hernández, and Nuria Gómez Blas. "Speed Proportional Integrative Derivative Controller: Optimization Functions in Metaheuristic Algorithms." Journal of Advanced Transportation 2021 (November 3, 2021): 1–12. http://dx.doi.org/10.1155/2021/5538296.

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Recent advancements in computer science include some optimization models that have been developed and used in real applications. Some metaheuristic search/optimization algorithms have been tested to obtain optimal solutions to speed controller applications in self-driving cars. Some metaheuristic algorithms are based on social behaviour, resulting in several search models, functions, and parameters, and thus algorithm-specific strengths and weaknesses. The present paper proposes a fitness function on the basis of the mathematical description of proportional integrative derivate controllers showing that mean square error is not always the best measure when looking for a solution to the problem. The fitness developed in this paper contains features and equations from the mathematical background of proportional integrative derivative controllers to calculate the best performance of the system. Such results are applied to quantitatively evaluate the performance of twenty-one optimization algorithms. Furthermore, improved versions of the fitness function are considered, in order to investigate which aspects are enhanced by applying the optimization algorithms. Results show that the right fitness function is a key point to get a good performance, regardless of the chosen algorithm. The aim of this paper is to present a novel objective function to carry out optimizations of the gains of a PID controller, using several computational intelligence techniques to perform the optimizations. The result of these optimizations will demonstrate the improved efficiency of the selected control schema.
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Nowak, M. "Improved aeroelastic design through structural optimization." Bulletin of the Polish Academy of Sciences: Technical Sciences 60, no. 2 (October 1, 2012): 237–40. http://dx.doi.org/10.2478/v10175-012-0031-8.

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Abstract. The paper presents the idea of coupled multiphysics computations. It shows the concept and presents some preliminary results of static coupling of structural and fluid flow codes as well as biomimetic structural optimization. The model for the biomimetic optimization procedure was the biological phenomenon of trabecular bone functional adaptation. Thus, the presented structural bio-inspired optimization system is based on the principle of constant strain energy density on the surface of the structure. When the aeroelastic reactions are considered, such approach allows fulfilling the mechanical theorem for the stiffest design, comprising the optimizations of size, shape and topology of the internal structure of the wing.
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Dissertations / Theses on the topic "Mechanical optimizations"

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Leong, Jonathan Yonghui. "Lubrication and tribological performance optimizations for micro-electro-mechanical systems." Thesis, Imperial College London, 2013. http://hdl.handle.net/10044/1/18067.

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Lubricants and lubrication have been of great interest to mankind since the introduction of machines with sliding/rolling surfaces into everyday life. With the recent trend of miniaturization, Micro-Electro-Mechanical Systems (MEMS) have taken centre stage, featuring components with scales in dimensions as small as nanometres. In this PhD study, two approaches to solving MEMS tribology problems have been pursued. First, a novel direct lubrication method using well-known lubricants such as perfluoropolyether (PFPE) and multiply alkylated cyclopentane (MAC) was developed and tested using reciprocating sliding and actual MEMS tribometry. The second approach utilized the concept of hydrodynamic lubrication and selective surface modification for MEMS. To combat spreading and starvation of lubricants in small contacts such as in MEMS, selective modification of the silicon surface with hydrophobic (non-wetting) and hydrophilic (wetting) portions was carried out and found to increase the force required to move a droplet of lubricant from a designated location on the surface. Octadecylamine and dodecylamine were also used as additives to successfully induce autophobicity in hexadecane, and the various spreading behaviours investigated. In conclusion, several new approaches to tackling tribological problems in MEMS have been researched. These methods are easily adapted to suitable MEMS devices and greatly reduce adhesion and friction, and increase wear and device life by several orders of magnitude.
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Gupta, Sandeep K. (Sandeep Kumar). "Protocol optimizations for the CRL distributed shared memory system." Thesis, Massachusetts Institute of Technology, 1996. http://hdl.handle.net/1721.1/41004.

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Gorsky, Daniel A. "Niyama Based Taper Optimizations in Steel Alloy Castings." Wright State University / OhioLINK, 2011. http://rave.ohiolink.edu/etdc/view?acc_num=wright1316191746.

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Smart, Ronald S. "Automated Multidisciplinary Optimizations of Conceptual Rocket Fairings." BYU ScholarsArchive, 2011. https://scholarsarchive.byu.edu/etd/3058.

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The purpose of this research is to develop and architect a preliminary multidisciplinary design optimization (MDO) tool that creates multiple types of generalized rocket fairing models. These models are sized relative to input geometric models and are analyzed and optimized, taking into account the primary objectives, namely the structural, thermal, and aerodynamic aspects of standard rocket flights. A variety of standard nose cone shapes is used as optimization proof of concept examples, being sized and compared to determine optimal choices based on the input specifications, such as the rocket body geometry and the specified trajectory paths. Any input models can be optimized to their respective best nose cone style or optimized to each of the cone styles individually, depending on the desired constraints. Two proof of concept example rocket model studies are included with varying sizes and speeds. Both have been optimized using the processes described to provide delineative instances into how results are improved and time saved. This is done by optimizing shape and thickness of the fairings while ascertaining if the remaining length downstream on the designated rocket model remains within specified stress and temperature ranges. The first optimized example exhibits a region of high stress downstream on the rocket body model that champions how these tools can be used to catch weaknesses and improve the overall integrity of a rocket design. The second example demonstrates how more established rocket designs can decrease their weight and drag through optimization of the fairing design.
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Tonoyan, Arsen V. "Finite element mesh optimization using genetic algorithms." Diss., The University of Arizona, 2004. http://hdl.handle.net/10150/280756.

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In finite element analysis, structures are modeled as meshes of elements and nodes appropriate for the geometry, boundaries and loading of each structure. Typically, it is desirable to have a mesh which is finer in parts of the structure where stress gradients are high and coarser where such gradients are low. This is usually done by experienced engineers using intuition and previous experience. Otherwise, a fine mesh throughout the structure can be used which results in high computational costs. In this work, the possibility of using genetic algorithms for optimizing finite-element meshes is studied. The method is implemented on a number of simple loaded structures. The meshes used are generated using a number of parameters that can be varied randomly. Then the parameters are varied using operators appropriate to genetic algorithms such that the value of an objective function is minimized within a defined precision and iteration limit. The objective function used in this study is an energy-based error norm. The results obtained with this method are compared to those obtained from a commercial finite element package that incorporates its own mesh optimization algorithms.
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DESHMUKH, DINAR VIVEK. "Design Optimization of Mechanical Components." University of Cincinnati / OhioLINK, 2002. http://rave.ohiolink.edu/etdc/view?acc_num=ucin1028738547.

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Vijayvargiya, Abhishek. "Multiobjective Optimization of Uncertain Mechanical Systems." Scholarly Repository, 2009. http://scholarlyrepository.miami.edu/oa_theses/224.

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This thesis is aimed at the optimum design of uncertain mechanical components and systems involving multiple objectives and constraints. There are various mechanical and design problems that are encountered every now and then which require the output that equalize several conflicting objectives. In recent years several methods have been developed to find a solution to multiobjective problems. The most efficient method for obtaining a compromise solution is the game theory method, which is based on the Pareto minimum or optimum solution. A thorough methodology is developed, and subsequently applied to three examples problems. The first problem is to design four helical springs which are further used to support a milling machine. The objective is to minimize the weight of the spring, also to minimize the deflection, and to maximize the natural frequency thus making the problem as a multiobjective problem. Further the subjected constraint is the shear stress constraint. After finding the optimized solution of the deterministic problem, the problem is again solved using Stochastic Nonlinear Programming, and after that it is solved using Interval Analysis. Game theory is used individually in all the three cases. The second problem is to design a gear box where the objectives are defined as the weight of the gear box, stress developed in the shaft 1, and the stress developed in shaft 2. It is subjected to nine constraints which are bending stress in teeth, contact stress of teeth, transverse displacement of shafts 1 and 2, and constraints related to the torque. The third problem is to design a power screw and the objective is to minimize the volume of the screw, and to maximize the critical buckling load and thus making it a multiobjective problem. It is subjected to constraints of being screw to be self locking, then the shear stress in screw thread, and the bearing stress in threads. The results of all the three problems that are achieved using Deterministic, Stochastic Nonlinear Programming, and Interval Analysis Method are tabulated, and the value of each objective achieved using these three methods for each problem at a time are compared to find out the most optimized solution.
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Lomangino, F. Paul. "Grammar- and optimization-based mechanical packaging." Diss., Georgia Institute of Technology, 1995. http://hdl.handle.net/1853/15848.

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Felden, Luc. "Mechanical optimization of vascular bypass grafts." Thesis, Available online, Georgia Institute of Technology, 2005, 2005. http://etd.gatech.edu/theses/available/etd-04112005-145422/unrestricted/felden%5Fluc%5F200505%5Fmast.pdf.

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Thesis (M. S.)--Mechanical Engineering, Georgia Institute of Technology, 2005.
David N. Ku, Committee Chair ; Alexander Rachev, Committee Co-Chair ; Elliot L. Chaikof, Committee Member. Includes bibliographical references.
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BONINI, Claudio. "Optimization Techniques Applied to Mechanical Design." Doctoral thesis, Università degli studi di Bergamo, 2014. http://hdl.handle.net/10446/30756.

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The present work deals with the application of optimization techniques to mechanical design. After an initial section devoted to a theoretical review of optimization algorithms in common use, the thesis consists of two parts. The first part is about the use of the adjoint method in the framework of aerodynamic shape optimization. After a theoretical review, the discrete adjoint method has been implemented in a research code based on the Discontinuous Galerkin (DG) method. This activity represents a new direction of development within the research group operating at University of Bergamo on DG methods for Computational Fluid Dynamics (CFD). Starting from the simple quasi-1D Euler equations, the implementation of the discrete adjoint method has been validated by comparing the values of computed adjoint variables with results of analytical solutions available in the literature. The method has then been applied to a shape optimization problem, using a gradient based algorithm with an inexact line search approach. The second part of the thesis deals with the application of optimization techniques to an industrial problem. This activity has been carried out at the R&D Centre of TenarisDalmine S.p.A., one of the largest seamless steel pipe producers in the world. This work focuses on the optimization of the thermal cycle of the mandrel of a longitudinal mandrel mill, with the objective of reducing the peak temperature of the mandrel during the rolling phase. The activity for this part of the thesis required the preliminary set up of a number of computational tools for the analysis of the physical aspects involved in the problem. Such tools have then been integrated in a comprehensive optimization approach driven by the optimization tools available in the Optimization Toolbox of the commercial software Matlab. The results of optimization are encouraging, showing the possibility of a considerable increase of the mandrel life cycle.
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Books on the topic "Mechanical optimizations"

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Haftka, Raphael T. Elements of Structural Optimization. Dordrecht: Springer Netherlands, 1990.

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Rao, R. Venkata, and Vimal J. Savsani. Mechanical Design Optimization Using Advanced Optimization Techniques. London: Springer London, 2012. http://dx.doi.org/10.1007/978-1-4471-2748-2.

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Rao, R. Venkata. Mechanical Design Optimization Using Advanced Optimization Techniques. London: Springer London, 2012.

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Angeles, J. Optimization of Cam Mechanisms. Dordrecht: Springer Netherlands, 1991.

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Banichuk, Nikolaĭ Vladimirovich. Structural optimization with uncertainties. Dordrecht: Springer, 2010.

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Statnikov, Roman B. Multicriteria Design: Optimization and Identification. Dordrecht: Springer Netherlands, 1999.

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Mistakidis, E. S., and G. E. Stavroulakis. Nonconvex Optimization in Mechanics. Boston, MA: Springer US, 1998. http://dx.doi.org/10.1007/978-1-4615-5829-3.

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Bestle, D., and W. Schiehlen, eds. IUTAM Symposium on Optimization of Mechanical Systems. Dordrecht: Springer Netherlands, 1996. http://dx.doi.org/10.1007/978-94-009-0153-7.

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Rozvany, G. I. N., ed. Topology Optimization in Structural Mechanics. Vienna: Springer Vienna, 1997. http://dx.doi.org/10.1007/978-3-7091-2566-3.

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Nonsmooth mechanics and convex optimization. Boca Raton, FL: CRC Press/Taylor & Francis, 2011.

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Book chapters on the topic "Mechanical optimizations"

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Hapuwatte, Buddhika M., Nehika Mathur, Noah Last, Vincenzo Ferrero, Maya Reslan, and K. C. Morris. "Optimizing Product Life Cycle Systems for Manufacturing in a Circular Economy." In Lecture Notes in Mechanical Engineering, 419–27. Cham: Springer International Publishing, 2023. http://dx.doi.org/10.1007/978-3-031-28839-5_47.

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AbstractGlobal population growth and increasing resource scarcity are necessitating sustainable manufacturing and circular economy (CE) practices. These practices require the decisions made at each product life cycle (PLC) stage consider sustainability and circularity implications. We propose PLC system level optimization to identify the most favorable choices, instead of siloed individual PLC stage-specific optimizations. This should yield better circularity by permitting manufacturers to take a more holistic view and identify the areas of highest impact across the PLC. This paper presents initial work towards building a PLC system optimization framework. From an initial review of current circularity metrics, we identify metrics that are suitable for forming the optimization objectives. Second, we identify decision variables available to manufacturers across the PLC that are useful in optimizing the entire system’s circularity and sustainability. Finally, we identify limitations of current metrics, and discuss major challenges and potential solutions to PLC system optimization problems.
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Chak, Vineet, V. M. S. Hussain, and Mayank Verma. "Optimizations of Process Parameters for Friction Stir Welding of Aluminium Alloy Al 7050." In Lecture Notes in Mechanical Engineering, 509–19. Singapore: Springer Singapore, 2020. http://dx.doi.org/10.1007/978-981-15-2696-1_50.

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Yaliwal, V. S., S. R. Daboji, K. N. Patil, M. K. Marikatti, and N. R. Banapurmath. "Multiple Optimizations of Engine Parameters of Single-Cylinder Four-Stroke Direct Injection Diesel Engine Operated on Dual Fuel Mode Using Biodiesel-Treated and Untreated Biogas Combination." In Lecture Notes in Mechanical Engineering, 765–93. Singapore: Springer Singapore, 2020. http://dx.doi.org/10.1007/978-981-15-5996-9_60.

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Statnikov, Roman B. "Multicriteria Approaches in Mechanical Engineering." In Applied Optimization, 57–110. Dordrecht: Springer Netherlands, 1999. http://dx.doi.org/10.1007/978-94-017-2363-3_4.

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Stavroulakis, Georgios E. "Computational Mechanics." In Applied Optimization, 11–54. Boston, MA: Springer US, 2001. http://dx.doi.org/10.1007/978-1-4615-0019-3_2.

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Mattheck, Claus, and Hans Kubler. "Mechanical Fundamentals." In Wood - The Internal Optimization of Trees, 2–20. Berlin, Heidelberg: Springer Berlin Heidelberg, 1997. http://dx.doi.org/10.1007/978-3-642-61219-0_2.

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Eberhard, Peter, Dieter Bestle, and Werner Schiehlen. "Optimization of Mechanical Systems." In Advanced Design of Mechanical Systems: From Analysis to Optimization, 237–52. Vienna: Springer Vienna, 2009. http://dx.doi.org/10.1007/978-3-211-99461-0_11.

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Cain, George. "Optimization Methods." In Mathematics for Mechanical Engineers, 10–1. Boca Raton: CRC Press, 2022. http://dx.doi.org/10.1201/9781003067672-10.

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Radermacher, Reinhard. "Thermal Systems Optimization." In Mechanical Engineers' Handbook, 554–72. Hoboken, NJ, USA: John Wiley & Sons, Inc., 2006. http://dx.doi.org/10.1002/0471777471.ch15.

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Fefferman, Charles L., and Luis A. Seco. "Interval Arithmetic in Quantum Mechanics." In Applied Optimization, 145–67. Boston, MA: Springer US, 1996. http://dx.doi.org/10.1007/978-1-4613-3440-8_7.

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Conference papers on the topic "Mechanical optimizations"

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Arpacioglu, Bertan, and Altan Kayran. "Comparative Structural Optimization Study of Composite and Aluminum Horizontal Tail Plane of a Helicopter." In ASME 2019 International Mechanical Engineering Congress and Exposition. American Society of Mechanical Engineers, 2019. http://dx.doi.org/10.1115/imece2019-11153.

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Abstract This work presents structural optimization studies of aluminum and composite material horizontal tail plane of a helicopter by using MSC. NASTRAN SOL200 optimization capabilities. Structural design process starts from conceptual design phase, and structural layout design is performed by using CATIA. In the preliminary design phase, study focuses on the minimum weight optimization with multiple design variables and similar constraints for both materials. Aerodynamic load calculation is performed using ANSYS and the finite element model of the horizontal tail plane is created by using MSC.PATRAN. According to the characteristics of materials, design variables are chosen. For the aluminum horizontal tail, thickness and flange areas are used as the design variables; and for composite horizontal tail, attention is mainly focused on the ply numbers and ply orientation angles of the laminated composite panels. By considering the manufacturability issues, discrete design variables are used. For three different mesh densities, different initial values of the design variables, and similar design constraints, optimizations are repeated and the results of optimizations are examined and compared with each other. In the optimizations performed, constraints are taken as strength and local buckling constraints. It is shown that the optimization methodology used in this study gives confident results for optimizing structures in the preliminary design phase.
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Alyaqout, Sulaiman F., Panos Y. Papalambros, and A. Galip Ulsoy. "Quantification and Use of System Coupling in Decomposed Design Optimization Problems." In ASME 2005 International Mechanical Engineering Congress and Exposition. ASMEDC, 2005. http://dx.doi.org/10.1115/imece2005-81364.

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Decomposition-based optimization strategies are used to solve complex engineering design problems that might be otherwise unsolvable. Yet, the associated computational cost can be prohibitively high due to the often large number of separate optimizations needed for coordination of problem solutions. To reduce this cost one may exploit the fact that some systems may be weakly coupled and their interactions can be suspended with little loss in solution accuracy. Suspending such interactions is usually based on the analyst’s experience or experimental observation. This article introduces an explicit measure of coupling strength among interconnected subproblems in a decomposed optimization problem, along with a systematic way for calculating it. The strength measure is then used to suspend weak couplings and thus improve system solution strategies, such as the model coordination method. Examples show that the resulting strategy can decrease the number of required system optimizations significantly.
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Heidtmann, Frank, and Dirk Soffker. "Numerical optimizations in observer-based monitoring of elastic mechanical systems." In 2008 International Conference on Prognostics and Health Management (PHM). IEEE, 2008. http://dx.doi.org/10.1109/phm.2008.4711459.

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Wang, Meng, Kihyung Kim, Michael R. von Spakovsky, and Douglas J. Nelson. "Use of State Space in the Dynamic Synthesis/Design and Operation/Control Optimization of a PEMFC System." In ASME 2008 International Mechanical Engineering Congress and Exposition. ASMEDC, 2008. http://dx.doi.org/10.1115/imece2008-68076.

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An often used approach to the synthesis/design optimization of energy systems is to only use steady state operation and high efficiency (or low total life cycle cost) at full load as the basis for the synthesis/design. Transient and partial load operations are considered secondarily by system and control engineers once the synthesis/design is fixed (i.e. system testing with standard load profiles). This paper considers the system dynamics from the very beginning of the synthesis/design process by developing the system using a set of transient thermodynamic, kinetic, geometric as well as cost models developed and implemented for the components of a 5 kW PEMFC (Proton Exchange Membrane Fuel Cell) system. The system is composed of three subsystems: a stack subsystem (SS), a fuel processing subsystem (FPS), and a work and air recovery subsystem (WRAS). In addition, state space is used in a looped set of optimizations to illustrate the effect of the control system on the synthesis/design optimization and to develop a set of optimal multi-input, multi-output (MIMO) controllers consistent with the optimal synthesis/design of the PEMFC system. It is shown that these MIMO controllers correspond to the ones found in a non-looped optimization in which the gains for the controllers are part of the decision variable set for the overall synthesis/design and operation/control optimization. These last set of results are then compared with the optimizations results found with the traditional approach of using a single load point in order to show the advantage of the dynamic optimization.
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Roberts, Kendric, and Yen-Lin Han. "Investigating Density Functional Theory’s Effectiveness in Studying Metal-Organic Frameworks Structures." In ASME 2019 International Mechanical Engineering Congress and Exposition. American Society of Mechanical Engineers, 2019. http://dx.doi.org/10.1115/imece2019-11013.

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Abstract In combatting human induced climate change, carbon capture provides the potential to more slowly ease away from the dependence on hydrocarbon fuel sources, while mitigating the amount of CO2 released into the atmosphere. One promising material to use is metal-organic frameworks (MOF’s). MOF’s offer an immense variety in potential exceptionally porous structures, a property important in separation. As a result of practical experimental measurements being expensive and time consuming, interest in accomplishing the same goal through modeling has also increased. Using density functional theory to optimize the approximate experimentally measured atomic geometries has been shown to have sufficient accuracy. A previous study by Nazarian et al. was performed to optimize structures on the CoRE MOF Database using a supercomputer. The purpose of this study was to attempt to replicate their work done with a single MOF using computational resources more commonly available. Furthermore, as time tends to be the limiting factor in conducting these studies, the use of a smearing function was adjusted for two optimizations to see if any considerable improvement on the efficiency of the optimizations could be made. Our results show both optimizations improved the bond length accuracy relative to the raw data compared with the optimization from Nazarian, et al. The optimization with a more present smearing effect was able to converge the electron field in roughly half the time, while still showing nearly the same results, except for slightly more variability in the bond lengths involving transition metals. Unfortunately, the improvement in bond length, did not correspond in consistent improvement of the larger cell defining metrics. This shows that either a different energy minimum was found or the relationship between the larger cell parameters, with the more local parameters such as bond length is too complex for the method to effectively solve.
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Muñoz, Jules R., and Michael R. von Spakovsky. "The Use of Decomposition for the Large Scale Synthesis/Design Optimization of Highly Coupled, Highly Dynamic Energy Systems: Part I—Theory." In ASME 2000 International Mechanical Engineering Congress and Exposition. American Society of Mechanical Engineers, 2000. http://dx.doi.org/10.1115/imece2000-1314.

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Abstract A general methodology for the decomposed optimization of highly coupled, highly dynamic energy systems is presented. The approach is based on the physical division of the system into units (sub-systems, components or disciplines) subject to functions describing the energy, cost and other couplings between them. Two versions of the approach are proposed. The first approach is called the Local-Global Optimization (LGO) Approach. LGO requires unit optimizations to be carried out with respect to purely local decision variables for various combinations of the functions that connect the units. The results are used to create an Optimum Response Surface (ORS) for the entire problem. The ORS is then searched by a system-level optimizer to find the values of the coupling functions that lead to an optimum system-level solution. The second approach proposed is an iterative version of LGO (ILGO). In this case, the ORS is closely approximated using a linear Taylor series expansion. The partial derivatives resulting from such an approximation are seen to correspond to the marginal costs typically used in the thermoeconomic literature. ILGO effectively and significantly reduces the number of unit optimizations required. The properties used to describe the coupling functions play a critical role in the convergence of ILGO to a global system-level optimum. A discussion of this and its implication for the choice of First or Second-Law based quantities for the optimization of systems is given.
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Neogi, Biswarup, Soumya Ghosal, Sinchan Ghosh, Tridib Kumar Bose, and Achintya Das. "Dynamic modeling and optimizations of mechanical prosthetic arm by simulation technique." In 2012 1st International Conference on Recent Advances in Information Technology (RAIT). IEEE, 2012. http://dx.doi.org/10.1109/rait.2012.6194542.

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Periannan, Vijayamand, Michael R. von Spakovsky, and David Moorhouse. "Investigation of the Effects of Various Energy and Exergy-Based Figures of Merit on the Optimal Design of a High Performance Aircraft System." In ASME 2006 International Mechanical Engineering Congress and Exposition. ASMEDC, 2006. http://dx.doi.org/10.1115/imece2006-14186.

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This paper shows the advantages of applying exergy-based analysis and optimization methods to the synthesis/design and operation of aircraft systems. In particular, an Advanced Aircraft Fighter (AAF) with three subsystems: a Propulsion Subsystem (PS), an Environmental Control Subsystem (ECS), and an Airframe Subsystem - Aerodynamics (AFS-A) is used to illustrate these advantages. Thermodynamic (both energy and exergy based), aerodynamic, geometric, and physical models of the components comprising the subsystems are developed and their interactions defined. Off-design performance is considered as well and is used in the analysis and optimization of system synthesis/design and operation as the aircraft is flown over an entire mission. An exergy-based parametric study of the PS and its components is first presented in order to show the type of detailed information on internal system losses which an exergy analysis can provide and an energy analysis by its very nature is unable to provide. This is followed by a series of constrained, system synthesis/design optimizations based on five different objective functions, which define energy-based and exergy-based measures of performance. The former involve minimizing the gross takeoff weight or maximizing the thrust efficiency while the latter involve minimizing the rates of exergy destruction plus the rate of exergy fuel loss (with and without AFS-A losses) or maximizing the thermodynamic effectiveness. A first set of optimizations involving four of the objecttives (two energy-based and two exergy-based) are performed with only PS and ECS degrees of freedom. Losses for the AFS-A are not incorporated into the two exergy-based objectives. The results show that as expected all four objectives globally produce the same optimum vehicle. A second set of optimizations is then performed with AFS-A degrees of freedom and again with two energy- and exergy-based objectives. However, this time one of the exergy-based objectives incorporates AFS-A losses directly into the objective. The results are that with this latter objective, a significantly better optimum vehicle is produced. Thus, an exergy-based approach is not only able to pinpoint where the greatest inefficiencies in the system occur but appears at least in this case to produce a superior optimum vehicle as well by accounting for irreversibility losses in subsystems (e.g., the AFS-A) only indirectly tied to fuel usage.
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Wang, Meng, Kihyung Kim, Michael R. von Spakovsky, and Douglas J. Nelson. "Multi- Versus Single-Level Dynamic Synthesis/Design and Operation/Control Optimizations of a PEMFC System." In ASME 2008 International Mechanical Engineering Congress and Exposition. ASMEDC, 2008. http://dx.doi.org/10.1115/imece2008-68073.

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As primary tools for the development of energy systems, optimization techniques have been studied for decades. However, for large-scale synthesis/design and operation/control optimization problems, it may turn out that it is impractical to solve the entire problem as a single optimization problem. In this paper, a multi-level optimization strategy, dynamic iterative local-global optimization (DILGO), is utilized for the synthesis/design and operation/control optimization of a 5 kWe PEMFC (Proton Exchange Membrane Fuel Cell) system. The strategy decomposes the system into three subsystems: a stack subsystem (SS), a fuel processing subsystem (FPS), and a work and air recovery subsystem (WRAS) and, thus, into three optimization sub-problems. To validate the decomposition strategy, the results are compared with a single-level dynamic optimization, in which the whole system is optimized together. In addition, for the purpose of comparison between different optimization algorithms, gradient-based optimization results are compared with those for a hybrid heuristic/gradient-based optimization algorithm.
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Cho, H. K., and R. E. Rowlands. "Minimizing Stress Concentrations in Laminated Composites by Genetic Algorithm." In ASME 2005 International Mechanical Engineering Congress and Exposition. ASMEDC, 2005. http://dx.doi.org/10.1115/imece2005-81005.

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Design optimizations using a genetic algorithm (GA) are well suited for problems having many design variables and local optimum design points. Concomitant with recent manufacturing advances, the concept is utilized here to minimize the tensile stress concentration in a perforated laminated composite by orientating the fibers locally both within the plies and from ply-to-ply. The current optimization approach is advantageously conducted in conjunction with FEA. The geometry is discretized into general 3D solid 20-node isoparametric layered composite elements of our own design. Solid, rather than plate, elements enable one to reliably account for features such as stress variations within and between individual plies. A parallel computing scheme is implemented between the FEA and GA optimization. Design optimization variables are local fiber directions within discrete finite elements and within respective plies of the laminate. Since fiber orientations are optimized locally within individual plies, the technique provides more than just a favorable stacking sequence of various rectilinearly orthotropic plies having different fiber orientations.
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Reports on the topic "Mechanical optimizations"

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Nian, H. L. T., T. M. Kuzay, and I. C. A. Sheng. Thermo-mechanical optimization of photon shutter 1 for APS front ends. Office of Scientific and Technical Information (OSTI), July 1992. http://dx.doi.org/10.2172/87839.

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Nian, H. L. T., T. M. Kuzay, and I. C. A. Sheng. Thermo-mechanical optimization of Fixed Mask 2 for APS front ends. Office of Scientific and Technical Information (OSTI), July 1992. http://dx.doi.org/10.2172/88506.

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Hamrick, Todd. Optimization of Operating Parameters for Minimum Mechanical Specific Energy in Drilling. Office of Scientific and Technical Information (OSTI), January 2011. http://dx.doi.org/10.2172/1060223.

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Tupek, Michael, and Brandon Talamini. Optimization-based algorithms for nonlinear mechanics and frictional contact. Office of Scientific and Technical Information (OSTI), September 2021. http://dx.doi.org/10.2172/1820695.

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Gu, Grace, Judith Alice Brown, and Joseph E. Bishop. Adjoint-based optimization of mechanical performance in polycrystalline materials and structures through texture control. Office of Scientific and Technical Information (OSTI), August 2017. http://dx.doi.org/10.2172/1375571.

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Krstulovich, S. F. Fermilab Central Computing Facility: Energy conservation report and mechanical systems design optimization and cost analysis study. Office of Scientific and Technical Information (OSTI), November 1986. http://dx.doi.org/10.2172/6941862.

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Krstulovich, S. F. Fermilab D-0 Experimental Facility: Energy conservation report and mechanical systems design optimization and cost analysis study. Office of Scientific and Technical Information (OSTI), October 1987. http://dx.doi.org/10.2172/5645921.

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Karasopoulos, Harry A., and Kevin J. Langan. Workshop on Trajectory Optimization Methods and Applications, Presentations from the 1992 AIAA Atmospheric Flight Mechanics Conference. Fort Belvoir, VA: Defense Technical Information Center, November 1992. http://dx.doi.org/10.21236/ada259761.

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DuPont, John N., Jeffrey D. Farren, Andrew W. Stockdale, and Brett M. Leister. Energy Saving Melting and Revert Reduction (E-SMARRT): Optimization of Heat Treatments on Stainless Steel Castings for Improved Corrosion Resistance and Mechanical Properties. Office of Scientific and Technical Information (OSTI), June 2012. http://dx.doi.org/10.2172/1045448.

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Engel, Bernard, Yael Edan, James Simon, Hanoch Pasternak, and Shimon Edelman. Neural Networks for Quality Sorting of Agricultural Produce. United States Department of Agriculture, July 1996. http://dx.doi.org/10.32747/1996.7613033.bard.

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The objectives of this project were to develop procedures and models, based on neural networks, for quality sorting of agricultural produce. Two research teams, one in Purdue University and the other in Israel, coordinated their research efforts on different aspects of each objective utilizing both melons and tomatoes as case studies. At Purdue: An expert system was developed to measure variances in human grading. Data were acquired from eight sensors: vision, two firmness sensors (destructive and nondestructive), chlorophyll from fluorescence, color sensor, electronic sniffer for odor detection, refractometer and a scale (mass). Data were analyzed and provided input for five classification models. Chlorophyll from fluorescence was found to give the best estimation for ripeness stage while the combination of machine vision and firmness from impact performed best for quality sorting. A new algorithm was developed to estimate and minimize training size for supervised classification. A new criteria was established to choose a training set such that a recurrent auto-associative memory neural network is stabilized. Moreover, this method provides for rapid and accurate updating of the classifier over growing seasons, production environments and cultivars. Different classification approaches (parametric and non-parametric) for grading were examined. Statistical methods were found to be as accurate as neural networks in grading. Classification models by voting did not enhance the classification significantly. A hybrid model that incorporated heuristic rules and either a numerical classifier or neural network was found to be superior in classification accuracy with half the required processing of solely the numerical classifier or neural network. In Israel: A multi-sensing approach utilizing non-destructive sensors was developed. Shape, color, stem identification, surface defects and bruises were measured using a color image processing system. Flavor parameters (sugar, acidity, volatiles) and ripeness were measured using a near-infrared system and an electronic sniffer. Mechanical properties were measured using three sensors: drop impact, resonance frequency and cyclic deformation. Classification algorithms for quality sorting of fruit based on multi-sensory data were developed and implemented. The algorithms included a dynamic artificial neural network, a back propagation neural network and multiple linear regression. Results indicated that classification based on multiple sensors may be applied in real-time sorting and can improve overall classification. Advanced image processing algorithms were developed for shape determination, bruise and stem identification and general color and color homogeneity. An unsupervised method was developed to extract necessary vision features. The primary advantage of the algorithms developed is their ability to learn to determine the visual quality of almost any fruit or vegetable with no need for specific modification and no a-priori knowledge. Moreover, since there is no assumption as to the type of blemish to be characterized, the algorithm is capable of distinguishing between stems and bruises. This enables sorting of fruit without knowing the fruits' orientation. A new algorithm for on-line clustering of data was developed. The algorithm's adaptability is designed to overcome some of the difficulties encountered when incrementally clustering sparse data and preserves information even with memory constraints. Large quantities of data (many images) of high dimensionality (due to multiple sensors) and new information arriving incrementally (a function of the temporal dynamics of any natural process) can now be processed. Furhermore, since the learning is done on-line, it can be implemented in real-time. The methodology developed was tested to determine external quality of tomatoes based on visual information. An improved model for color sorting which is stable and does not require recalibration for each season was developed for color determination. Excellent classification results were obtained for both color and firmness classification. Results indicted that maturity classification can be obtained using a drop-impact and a vision sensor in order to predict the storability and marketing of harvested fruits. In conclusion: We have been able to define quantitatively the critical parameters in the quality sorting and grading of both fresh market cantaloupes and tomatoes. We have been able to accomplish this using nondestructive measurements and in a manner consistent with expert human grading and in accordance with market acceptance. This research constructed and used large databases of both commodities, for comparative evaluation and optimization of expert system, statistical and/or neural network models. The models developed in this research were successfully tested, and should be applicable to a wide range of other fruits and vegetables. These findings are valuable for the development of on-line grading and sorting of agricultural produce through the incorporation of multiple measurement inputs that rapidly define quality in an automated manner, and in a manner consistent with the human graders and inspectors.
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