Thermal performance optimization of Si micro flat heat pipes by Box–Behnken design

Microsystem Technologies - Si micro heat pipe (MHP) is become an excellent passive cooling device for thermal management of micro electronics packages because of its considerable thermo-mechanical...     

Application of particle swarm optimization algorithm in bellow optimum design

In this paper, Particle Swarm Optimization Algorithm （PSOA） is used in problem of the bellow optimum design with constraints, in which the design variables are discrete. To implement bellow optimum design by PSOA, an augmented objective function is constructed based on penalty function and a new updating scheme of penalty parameter s is proposed. A new Discrete PSOA （DPSOA） is proposed. The mathematic model of bellow optimum design is established. Through numerical examples of bellow design, comparing the results of examples by proposed DPSOA with the theory solutions by Net method, it shows that the particle swarm optimization algorithm can be applied to the bellow optimum design successfully and satisfactory results by DPSOA are obtained, which is discrete optimal solution in the feasible domain.     

Object-oriented design of process line simulation and optimization—A case study in papermaking

Simulation-based optimization for industrial process lines is discussed in this paper. Our approach combines multidisciplinary modeling, modern sensitivity analysis methodology as well as multiobjective optimization by means of object-oriented software design principles. As a result, a simulation and optimization approach that can be extended and modified due to users’ needs can be developed. Our approach is illustrated by a real-world example from papermaking industry.     

Application of mathematical programming in the design of optimal control systems†

The problem of applying the various computational methods of mathematical programming in the design of an optimal control system is discussed. A general case of non-linear, non-autonomous, state equations, subject to inequality constraints on both state and control variables, is considered. Both continuous and discrete time systems are investigated. In case of discrete time systems, the sampling intervals are assumed generally unequal and aperiodic, with inequality constraints imposed upon them.

Systems like these impose considerable computational difficulties when treated by the maximum principle or dynamie programming. Using mathematical programming, one may simplify a wide class of those computational problems.

Several examples of applying mathematical programming to particular control problems are presented.     

Multi-objective optimization design of a connection frame in macro–micro motion platform

Connection frame is an essential component to implement high acceleration and ultra-precision positioning motion in a macro–micro motion platform. The performance of the positioning system is mainly affected by two sources which include thermal–mechanical deformation and the natural frequency of connection frame. In the paper, multi-objective optimization and design for the connection frame is constructed and discussed comprehensively by the effects of thermal–mechanical deformation and the natural frequency of the system. The optimization objectives for the connection structure are the minimized displacement when thermal–mechanical deformation is occurred, the maximized natural frequency to avoid system resonance, and the light weight for the connection structure to fulfil high acceleration motion. Using response surface method (RSM) combined with finite element method (FEM), the objective function is formulated as a prediction model. Non-dominated Sorting Genetic Algorithm II (NSGAII) is used to solve the optimization model and attain the matched parameters. A cantilever beam example is tested to examine the validity of the methodology, and the results from prediction model agree well with that from theoretical model. By the above methodology, a high performance with optimal parameters for the connection structure is obtained, and its natural frequency and weight can meet our design expectation.     

Application of the QFD as a design approach to ensure comfort in using hand tools: Can the design team complete the House of Quality appropriately?

Quality Function Deployment is proposed as an effective design method to integrate ergonomics needs and comfort into hand tool design because it explicitly addresses the translation of customer needs into engineering characteristics. A crucial step during QFD concerns the linking of engineering characteristics to customer needs in the House of Quality by the design team. It is generally assumed (looking at all the QFD success stories) that design teams can accurately predict the correlations between customer needs and engineering characteristics (also referred to as “Whats”/“Hows” correlations). This paper explicitly tests this assumption by comparing the “Whats”/“Hows” correlations estimated by a design team with those observed in a systematic user evaluation study, which has not been done before. Testing the assumption is important, because inaccurate estimates may lead to ergonomically ineffective (re)design of hand tools and a waste of company resources. Results revealed that the design team's correlation estimates were not as accurate as is generally assumed. Twenty-five percent of the estimates differed significantly with those observed in the user evaluation study. Thus, QFD is a useful method to assist design teams in designing ergonomically more comfortable hand tools, but only on the condition that the correlations between customer needs and engineering characteristics are validated, preferably by means of a systematic user evaluation study.     

Robust topology optimization of structures with uncertainties in stiffness – Application to truss structures

A computational strategy is proposed for robust structural topology optimization in the presence of uncertainties with known second order statistics. The strategy combines deterministic topology optimization techniques with a perturbation method for the quantification of uncertainties associated with structural stiffness, such as uncertain material properties and/or structure geometry. The use of perturbation transforms the problem of topology optimization under uncertainty to an augmented deterministic topology optimization problem. This in turn leads to significant computational savings when compared with Monte Carlo-based optimization algorithms which involve multiple formations and inversions of the global stiffness matrix. Examples from truss structures are presented to show the importance of including the effect of controlling the variability in the final design. It is also shown that results obtained from the proposed method are in excellent agreement with those obtained from a Monte Carlo-based optimization algorithm.     

The power of computational thermochemistry in high-temperature process design and optimization: Part 1 — Unit operations

Industrial process modeling is increasingly accessible through computational chemistry packages. Computational Thermochemistry (CT) is particularly convenient for exploring the behavior of high-temperature processes (e.g., pyrometallurgical unit operations such as calciners, roasters, smelters, converters, and electric arc furnaces) since their operating conditions are mostly dictated by local/global thermodynamic phase equilibria. Under these high-temperature conditions, energy barriers are small and do not limit the kinetics of many chemical reactions. In this context, engineers-in-training must take full advantage of CT to explore and understand current unit operations in high-temperature manufacturing technologies. This work illustrates the strength of computational thermochemistry for high-temperature modeling through four case studies, i.e., 1. a carbo-reduction process, 2. a glass production/recycling furnace, 3. an aluminothermic reactor for the production of a ferroniobium alloy, and 4. a titanium purification unit. Moreover, the relevance of key fundamental thermodynamic concepts is discussed through the modeling of these unit operations. All the thermodynamic simulations presented in this work were performed using FactSage, a metallurgy-specialized thermochemical package widely employed in both academia and industry.     

Robust shaft design to compensate deformation in the hub press-fitting and disk clamping process of 2.5″ HDDs

We investigated deformation of the outer diameter of a shaft due to the hub press-fitting and disk clamping processes associated with a 2.5″ hard disk drive. We propose a new robust shaft design to minimize the effect of deformation on the outer diameter of the shaft. We numerically show the effect of deformation on the shaft due to the pressure, stiffness, and damping coefficients of fluid dynamic bearings (FDBs), and the critical mass and excitation response of the rotor-bearing system. We also experimentally measured the axial non-repeatable runout and the amplitude at the half speed whirl frequency of FDBs with both conventional and proposed designs. Through these tests we confirm that the proposed design improves the static and dynamic performance of the FDBs and rotor-bearing system.     

Exploration of trade-offs in the design of volatile STT–RAM cache

STT–RAM is considered as a promising alternative to SRAM due to its low static power (non-volatility) and high density. However, write operation of STT–RAM is inefficient in terms of energy and speed compared to SRAM and thus various device-/circuit-/architecture-level solutions have been proposed to tackle this inefficiency. One of the proposed solutions is redesigning STT–RAM cell for better write characteristics at the cost of shortened retention time (volatile STT–RAM). Because the retention failure of STT–RAM has a stochastic property, an extra overhead of periodic scrubbing with error correcting code (ECC) is required to tolerate the failure. The more frequent scrubbing and stronger ECC are used, the shorter retention time is allowed. With an analysis based on analytic STT–RAM model, we have conducted extensive experiments on various volatile STT–RAM cache design parameters including scrubbing period, ECC strength, and target failure rate. The experimental results show the impact of the parameter variations on last-level cache energy and performance and provide a guideline for designing a volatile STT–RAM with ECC and scrubbing.     

Grading in interaction design education using design practitioners’ conceptions of process quality

The designed product is often assessed in interaction design education, but there are also courses that focus on learning the design process. It is then necessary to develop criteria for grading in such courses. To make a successful transfer from theory to practice, students also need to learn the criteria practitioners use, rather than the criteria that academically oriented teachers use. To do this, one approach is to align criteria with the conceptions practicing interaction designers have of process quality in design. Therefore, the research questions for this study are what those conceptions are, and how they can be utilized in grading criteria for interaction design projects in education. Interviews were made with 10 interaction designers. The interviews were qualitatively analyzed. The results demonstrate that practicing interaction designers conceptualize the quality of the design process in three ways: it is good if established methods are used and the design is managed within resource constraints, and within organizational and technological limitations, while also meeting stated objectives; it is even better if the design has a thought-through rationale; and ideally, the design should also be inspirational. These conceptions were transferred to points on a criteria-referenced grading scale which was used to develop course specific grading criteria. The criteria were evaluated in terms of comprehensibility and reliability. The evaluation showed that most of the students who also attended lectures understood the criteria. A high and significant covariation and a high level of agreement between the two teachers who graded the projects were shown. Further, the developed criteria should be generalizable to other process-centered interaction design courses and to assessment in other design disciplines.     

Thermodynamic optimization of the As–S system

Literature review, critical assessment and thermodynamic modeling of the liquid and solid phases in the As–S system are presented. A set of optimized model parameters was obtained to reproduce previously published experimental data. The literature data included enthalpies of formation, heat capacity, vapor pressure and phase equilibrium data. A significant discrepancy among different sets of literature data was revealed. The model for the liquid phase was developed within the framework of the Modified Quasichemical Model (MQM) in pair approximation. The resulting set of model parameters was merged and tested within a larger multicomponent thermodynamic database for pyrometallurgical copper, lead and recycling industrial operations.     

A posteriori optimization of parameters in stabilized methods for convection–diffusion problems – Part I

Stabilized finite element methods for convection-dominated problems require the choice of appropriate stabilization parameters. From numerical analysis, often only their asymptotic values are known. This paper presents a general framework for optimizing stabilization parameters with respect to the minimization of a target functional. Exemplarily, this framework is applied to the SUPG finite element method and the minimization of a residual-based error estimator, an error indicator, and a functional including the crosswind derivative of the computed solution. Benefits of the basic approach are demonstrated by means of numerical results.     

Control–structural design optimization for vibration of piezoelectric intelligent truss structures

Based on the design sensitivity analysis for structural dynamics in time domain, an integrated control–structural design optimization method is proposed to the vibration control of piezoelectric intelligent truss structure. In this investigation, the objective function and constraint functions include not only the conventional design indexes of structure but also the vibration control indexes and the feedback control variables. The structural design variables are optimized simultaneously with the vibration control system. The sensitivity relations for the control–structure optimization model are derived by using a new method, and the sequential linear programming algorithm is used to solve this kind of optimization problem. The numerical examples given in the paper demonstrate the effectiveness of methods and the program.