Material design of elastic structures using Voronoi cells

New tools for the design of metamaterials with periodic microarchitectures are presented. Initially, a two‐scale material design approach is adopted. At the structure scale, the material effective properties and their spatial distribution are obtained through a Free Material Optimization technique. At the microstructure scale, the material microarchitecture is designed by appealing to a Topology Optimization Problem (TOP). The TOP is based on the topological derivative and the level set function. The new proposed tools are used to facilitate the search of the optimal microarchitecture configuration. They consist of the following: (i) a procedure to choose an adequate shape of the unit cell domain where the TOP is formulated and shapes of Voronoi cells associated with Bravais lattices are adopted and (ii) a procedure to choose an initial material distribution within the Voronoi cell being utilized as the initial configuration for the iterative TOP.     

La2 CuO4前驱物粉体的自蔓延燃烧合成及其晶化

分别采用硝酸盐自蔓延燃烧法和醋酸盐／硝酸盐自蔓延燃烧法低温合成了La2CuO4前驱物粉体,研究了在不同条件下制备的前驱物粉体的晶化行为。在硝酸盐自蔓延燃烧法合成前驱物粉体时,燃烧反应十分剧烈,在前驱物粉体中发现有Cu单质存在,Cu单质的存在不利于在低温合成单一相La2CuO4粉体。在硝酸盐自蔓延燃烧法基础上,以醋酸盐部分取代硝酸盐,大幅度降低了自蔓延燃烧温度,可以通过调整尿素的用量来改变氧化剂的总氧化价O与还原剂的总还原价F之比,使自蔓延燃烧温度连续可调。用醋酸盐／硝酸盐自蔓延燃烧法合成的前驱物粉体在较低温度焙烧处理,得到了单一相La2CuO4粉体。自蔓延燃烧温度对前驱物的组成和焙烧产物的组成和显微形貌有显著影响。自蔓延燃烧温度连续可调为得到具有可控制显微形貌的目标产物提供了可能。     

单片机用单端反激式隔离开关稳压电源的设计

基于TOP224Y单片开关电源控制芯片,提出了一种适于单片机控制系统的单端反激式开关稳压电源,实现了 5V, 15V双路输出。文中根据TOP224Y的特性,给出了单端反激式开关电源的工程设计方法,结合单片机供电特点对其外围电路进行了分析和讨论,并在实验的基础上对该电路的性能进行了验证。     

CUSUM charts with controlled conditional performance under estimated parameters

We study the effect of the Phase I estimation error on the cumulative sum (CUSUM) chart. Impractically large amounts of Phase I data are needed to sufficiently reduce the variation in the in-control average run lengths (ARL) between practitioners. To reduce the effect of estimation error on the chart's performance we design the CUSUM chart such that the in-control ARL exceeds a desired value with a specified probability. This is achieved by adjusting the control limits using a bootstrap-based design technique. Such approach does affect the out-of-control performance of the chart; however, we find that this effect is relatively small.     

Tolerancing of board-level-free-space optical interconnects

For optical interconnects to become a mature technology they must be amenable to electronic packaging technology. Two main obstacles to including free-space optical interconnects are alignment and heat-dissipation issues. Here we study the issues of alignment tolerancing that are due to assembly and manufacturing variations (passive-element tolerancing) over long board-level distances (>10 cm) for free-space optical interconnects. We also combine these variations with active optoelectronic device variations (active-element tolerancing). We demonstrate a computer-aided analysis procedure that permits one to determine both active- and passive-element tolerances needed to achieve some system-level specification, such as yield or cost. The procedure that we employ relies on developing a detailed design of the system to be studied in a standard optical design program, such as code v. Using information from this model, we can determine the integrated power falling on the detector, which we term optical throughput, by performing Gaussian propagation or general Fresnel propagation (if significant vignetting occurs). This optical throughput can be used to determine system-level performance criteria, such as bit-error rate. With this computer-aided analysis technique, a sensitivity analysis of all the variations under study is made on a system with realistic board-level interconnect distances to find each perturbation's relative effects (with other perturbations set to 0) on the power falling on the detector. This information is used to set initial tolerances for subsequent tolerancing analysis and design runs. A tolerancing analysis by Monte Carlo techniques is applied to determine if the yield or cost (yield is denned as the percentage of systems that have acceptable system performance) is acceptable. With a technique called parametric sampling, a subsequent tolerancing design run can be applied to optimize this yield or cost with little increase in computation. We study a design example and show that most of the tolerances can be achieved with current technology.     

Enhanced exact solution methods for the Team Orienteering Problem

The Team Orienteering Problem (TOP) is one of the most investigated problems in the family of vehicle routing problems with profits. In this paper, we propose a Branch-and-Price approach to find proven optimal solutions to TOP. The pricing sub-problem is solved by a bounded bidirectional dynamic programming algorithm with decremental state space relaxation featuring a two-phase dominance rule relaxation. The new method is able to close 17 previously unsolved benchmark instances. In addition, we propose a Branch-and-Cut-and-Price approach using subset-row inequalities and show the effectiveness of these cuts in solving TOP.     

Cutting the double loop: Theory and algorithms for reliability-based design optimization with parametric uncertainty

Parametric uncertainties complicate engineering design—confounding regulated design approaches and degrading the performance of reliability efforts. The simplest means to tackle this uncertainty is double-loop simulation , a nested Monte Carlo method that, for practical problems, is intractable. In this work, we introduce a flexible, general approximation technique that obviates the double loop. This approximation is constructed in the context of a novel theory of reliability design under parametric uncertainty: we introduce metrics for measuring the efficacy of reliability-based design optimization strategies ( epistemic design gap and effective reliability ), minimal conditions for controlling uncertain reliability ( precision margin ), and stricter conditions that guarantee the desired reliability at a designed confidence level. We provide a number of examples with open-source code to demonstrate our approaches in a reproducible fashion.     

Multivariate tolerance design for a quadratic design parameter model

The determination of tolerance allocations among design parameters is an integral phase of product/process design. Such allocations are often necessary to achieve desired levels of product performance. Parametric and nonparametric methods have recently been developed for allocating multivariate tolerances. Parametric methods assume full information about the probability distribution of design parameter processes, whereas, nonparametric methods assume that only partial information is available, which consists of only design parameter process variances. These methods currently assume that the relationship between the design parameters and each of the performance measures is linear. However, quadratic response functions are increasingly being used to provide better approximations of the relationships between performance measures and design parameters. This is especially prevalent where there is a multivariate set of performance measures that are functions of a common set of design parameters. In this research we propose both parametric and nonparametric multivariate tolerance allocation procedures which consider the more general case where these relationships can be represented by quadratic functions of the design parameters. We develop the corresponding methodology and nonlinear optimization models to accommodate and take advantage of the presence of interactions and other nonlinearities among suppliers.     

Modelling,measurement and evaluation of sequencing flexibility in manufacturing systems

Sequencing flexibility refers to the possibility of interchanging the order in which required manufacturing operations are performed. In this paper, we address several issues related to the modelling, measurement and performance evaluation of this flexibility in manufacturing systems. In particular, we introduce several representation and measurement schemes for sequencing flexibility and discuss the usefulness and limitations each. We then propose a new performance-based approach for quantifying the value of flexibility. To this effect, we study the relationship between flexibility and system performance under a variety of design assumptions and operating conditions. These relationships are used to identify key characteristics of a measure of flexibility that is reflective of system performance. This measure is to allow system designers and managers to predict performance based on existing levels of flexibility and/or determine the amount of flexibility required to achieve a certain level of performance. This measure is shown to be easier to calculate than traditional performance measures and to be possible to use as a substitute for these measures in estimating the effect of flexibility on performance.     

Engineering design optimization using species-conserving genetic algorithms

The species conservation technique described here, in which the population of a genetic algorithm is divided into several groups according to their similarity, is inspired by ecology. Each group with similar characteristics is called a species and is centred on a dominating individual, called the species seed. A genetic algorithm based on this species conservation technique, called the species-conserving genetic algorithm (SCGA), was established and has been proved to be effective in finding multiple solutions of multimodal optimization problems. In this article, the SCGA is used to solve engineering design optimization problems. Different distance measures (measures of similarity) are investigated to analyse the performance of the SCGA. It is shown that the Euclidean distance is not the only possible basis for defining a species and sometimes may not make sense in engineering applications. Two structural design problems are used to demonstrate how the choice of a meaningful measure of similarity will help the exploration for significant designs.     

Proactive environmental strategies and performance: role of green supply chain processes and green product design in the Chinese high-tech industry

Though many firms still believe that passive environmental strategies are sufficient, it is pertinent that they move beyond this belief and take a proactive supply chain-wide environmental stance so as to create a sustainable environment. In this paper, we seek to extend current work within green supply chain management by considering multiple green supply chain capabilities and performance measures. We hypothesise the linkage between environmental orientation, green supply chain capabilities and performance by drawing upon stakeholder theory and natural resource-based view. More importantly, our study is the first to distinguish between product and process-related capabilities in the green supply chain area and study their direct and mediating role with respect to environmental and financial performance measures. Using survey data collected from 256 Chinese-based high-tech firms, we analyse several hypothesised relationships. Our results provide strong support for the significant role that green product design and green supply chain processes can play in improving firms’ environmental and financial performance. Interestingly, our results also suggest that green product design may not have a direct impact on financial performance.     

Time of flight spectrometer with optical polarizer for cold pulsed neutrons

We describe a new TOF spectrometer (named TOP) installed at the pulsed spallation neutron source at KENS. Pulsed neutrons moderated by solid methane (cooled to 20 K) and transmitted by a guide tube were polarized by a Soller array of curved mirrors. The performance and the detailed instrumentation are summarized.     

Analyzing transformation-based simulation metamodels

To analyze a simulation (response surface) metamodel that involves a variance-stabilizing transformation of the original simulation-generated response, we present two techniques. In the first technique we compute an approximate percentile-type confidence interval for the mean of the original response at a selected factor-level combination (design point) as follows: we compute the usual confidence interval for the mean of the transformed response at that design point; and then we untransform the corresponding endpoints to obtain the desired confidence interval for the untransformed metamodel. In the second technique we compute the Maximum Likelihood Estimator (MLE) for the mean of the untransformed response based on standard distributional properties of the transformed metamodel; then using the delta method to approximate the MLE's variance, we construct for the untransformed metamodel an asymptotically exact confidence interval centered on the MLE. We illustrate these techniques in a case study on manufacturing cell design, comparing them with a more conventional approach for analyzing transformed-based simulation metamodels. A Monte Carlo performance evaluation shows that significantly better confidence-interval coverage is maintained with the second proposed technique (called the "MLE-delta method") over a wide range of values for the residual variance of the transformed metamodel.     

Acousto-optical wideband correlator system: design, implementation, and evaluation

We describe the design and development of an acousto-optical wideband correlator that we integrated into a digital signal-processing system testbed. We report its measured performance and compare it with various theoretical performance measures, one of which compares the optical system with an equivalent efficient digital correlator. The measured performance of the optical system was 20 to 70 times that of a VAX 6410 computer using a fast-Fourier-transform correlation algorithm and a vector processor, even though the electronic interface system limited the performance of the optical system to less than 0.5% of its potential. We also compare the system with commercially available digital signal-processing boards.     

Tolerance optimization of a mobile phone camera lens system

In the manufacturing process for the lens system of a mobile phone camera, various types of assembly and manufacturing tolerances, such as tilt and decenter, should be appropriately allocated. Because these tolerances affect manufacturing cost and the expected optical performance, it is necessary to choose a systematic design methodology for determining optimal tolerances. In order to determine the tolerances that minimize production cost while satisfying the reliability constraints on important optical performance indices, we propose a tolerance design procedure for a lens system. A tolerance analysis is carried out using Latin hypercube sampling for evaluating the expected optical performance. The tolerance optimization is carried out using a function-based sequential approximate optimization technique that can reduce the computational burden and smooth numerical noise occurring in the optimization process. Using the proposed design approach, the optimal production cost was decreased by 28.3% compared to the initial cost while satisfying all the constraints on the expected optical performance. We believe that the tolerance analysis and design procedure presented in this study can be applied to the tolerance optimization of other systems.     

Supplier involvement in new product development projects: dimensionality and contingency effects

In contrast to previous literature, we hypothesize supplier involvement in new product development (NPD) projects to be multidimensional in nature and test this assumption using data from a large sample of NPD projects. We also test the contingent influence of supplier involvement on NPD project performance. The results supported the claim of multidimensionality of supplier involvement. Three distinct factors–communication and information sharing, design involvement and infrastructure–comprising supplier involvement were found. These factors were significantly related to one or more measures of NPD project performance. The study also found support for the contingent influence of market stability on the supplier involvement–NPD project performance relationships. The results suggest that managers ought to consider adopting different bundles of supplier involvement practices that depend on the level of stability in markets and also on the type of NPD performance objective that is being considered.     

Low-Density Parity-Check Coded Recording Systems With Run-Length-Limited Constraints

We propose two techniques for the low-density parity-check (LDPC) coded partial response channel with run-length-limited (RLL) constraints. The first is a modification of the selective flipping technique so that side information is not needed. The second is based on the estimation of flipped bits for the selective flipping technique. The second technique can achieve significant performance improvement over the simple selective flipping technique either with side information or without side information. We also incorporate these two techniques into a known technique to design LDPC coded recording systems that can meet strict RLL constraints without performance degradation.      

Design of loading policies for a high-performance computer system

We use a systematic simulation study of computer-system loading policies to design a loading policy for a high-performance system. Our results illustrate the performance advantages of 'round-robin' disciplines, the interference caused by finite memory, and how this interference can be mitigated by using carefully selected loading policies that exploit information about job resource requirements. Our choice of performance measures allows us to assess response-time predictability and fairness as well as overall efficiency. Using the insights obtained from our study, we introduce a new type of policy, the NEST policy, which is structured to employ the principles of good scheduling, while avoiding shortcomings of commonly used approaches.     

DISTINÏCT: Data poISoning atTacks dectectIon usiNg optÏmized jaCcarddisTance

Machine Learning (ML) systems often involve a re-training process to make better predictions and classifications. This re-training process creates a loophole and poses a security threat for ML systems. Adversaries leverage this loophole and design data poisoning attacks against ML systems. Data poisoning attacks are a type of attack in which an adversary manipulates the training dataset to degrade the ML system’s performance. Data poisoning attacks are challenging to detect, and even more difficult to respond to, particularly in the Internet of Things (IoT) environment. To address this problem, we proposed DISTINÏCT, the first proactive data poisoning attack detection framework using distance measures. We found that Jaccard Distance (JD) can be used in the DISTINÏCT (among other distance measures) and we finally improved the JD to attain an Optimized JD (OJD) with lower time and space complexity. Our security analysis shows that the DISTINÏCT is secure against data poisoning attacks by considering key features of adversarial attacks. We conclude that the proposed OJD-based DISTINÏCT is effective and efficient against data poisoning attacks where in-time detection is critical for IoT applications with large volumes of streaming data.     

Lidar technique for remote measurement of temperature by use of vibrational-rotational Raman spectroscopy

Atmospheric temperature can be measured remotely by a lidar system that measures the ratio of backscattered signals from vibrational-rotational Raman scattering by N(2) to pure vibrational Raman scattering. We present simulations of the performance of an airborne lidar system (based on the Goddard Airborne Raman lidar) that employs this technique.