Conceptual Design and Workspace Analysis of an Exechon-inspired Parallel Kinematic Machine

Inspired by the commercial application of the Exechon machine, this paper proposed a novel parallel kinematic machine (PKM) named Exe-Variant. By exchanging the sequence of kinematic pairs in each limb of the Exechon machine, the Exe-Variant PKM claims an arrangement of 2UPR/1SPR topology and consists of two identical UPR limbs and one SPR limb. The inverse kinematics of the 2UPR/1SPR parallel mechanism was firstly analyzed based on which a conceptual design of the Exe-Variant was carried out. Then an algorithm of reachable workspace searching for the Exe-Variant and the Exchon was proposed. Finally, the workspaces of two example systems of the Exechon and the Exe-Variant with approximate dimensions were numerically simulated and compared. The comparison shows that the Exe-Variant possesses a competitive workspace with the Exechon machine, indicating it can be used as a promising reconfigurable module in a hybrid 5-DOF machine tool system.

Stiffness Analysis and Experiment of a Novel 5-DoF Parallel Kinematic Machine Considering Gravitational Effects

In order to carry out high-precision machining of aerospace structural components with large size, thin wall and complex surface, this paper proposes a novel parallel kinematic machine (PKM) and formulates its semi-analytical theoretical stiffness model considering gravitational effects that is verified by stiffness experiments. From the viewpoint of topology structure, the novel PKM consists of two substructures in terms of the redundant and overconstrained parallel mechanisms that are connected by two interlinked revolute joints. The theoretical stiffness model of the novel PKM is established based upon the virtual work principle and deformation superposition principle after mapping the stiffness models of substructures from joint space to operated space by Jacobian matrices and considering the deformation contributions of interlinked revolute joints to two substructures. Meanwhile, the component gravities are treated as external payloads exerting on the end reference point of the novel PKM resorting to static equivalence principle. This approach is proved by comparing the theoretical stiffness values with experimental stiffness values in the same configurations, which also indicates equivalent gravity can be employed to describe the actual distributed gravities in an acceptable accuracy manner. Finally, on the basis of the verified theoretical stiffness model, the stiffness distributions of the novel PKM are illustrated and the contributions of component gravities to the stiffness of the novel PKM are discussed.

Elastodynamic Modeling and Analysis for an Exechon Parallel Kinematic Machine

As a newly invented parallel kinematic machine (PKM), Exechon has attracted intensive attention from both academic and industrial fields due to its conceptual high performance. Nevertheless, the dynamic behaviors of Exechon PKM have not been thoroughly investigated because of its structural and kinematic complexities. To identify the dynamic characteristics of Exechon PKM, an elastodynamic model is proposed with the substructure synthesis technique in this paper. The Exechon PKM is divided into a moving platform subsystem, a fixed base subsystem and three limb subsystems according to its structural features. Differential equations of motion for the limb subsystem are derived through finite element (FE) formulations by modeling the complex limb structure as a spatial beam with corresponding geometric cross sections. Meanwhile, revolute, universal, and spherical joints are simplified into virtual lumped springs associated with equivalent stiffnesses and mass at their geometric centers. Differential equations of motion for the moving platform are derived with Newton's second law after treating the platform as a rigid body due to its comparatively high rigidity. After introducing the deformation compatibility conditions between the platform and the limbs, governing differential equations of motion for Exechon PKM are derived. The solution to characteristic equations leads to natural frequencies and corresponding modal shapes of the PKM at any typical configuration. In order to predict the dynamic behaviors in a quick manner, an algorithm is proposed to numerically compute the distributions of natural frequencies throughout the workspace. Simulation results reveal that the lower natural frequencies are strongly position-dependent and distributed axial-symmetrically due to the structure symmetry of the limbs. At the last stage, a parametric analysis is carried out to identify the effects of structural, dimensional, and stiffness parameters on the system's dynamic characteristics with the purpose of providing useful information for optimal design and performance improvement of the Exechon PKM. The elastodynamic modeling methodology and dynamic analysis procedure can be well extended to other overconstrained PKMs with minor modifications.

Diagnostic value of increased sensitivity by massively parallel sequencing

Routine molecular diagnostics modalities are unable to confidently detect low frequency mutations (<5-15%) that may indicate response to targeted therapies. We confirm the presence of a low frequency NRAS mutation in a rectal cancer patient using massively parallel sequencing when previous Sanger sequencing results proved negative and Q-PCR testing inconclusive. There is increasing evidence that these low frequency mutations may confer resistance to anti-EGFR therapy. In view of negative/inconclusive Sanger sequencing and Q-PCR results for NRAS mutations in a KRAS wt rectal case, the diagnostic biopsy and 4 distinct subpopulations of cells in the resection specimen after conventional chemo/radiotherapy were massively parallel sequenced using the Ion Torrent PGM. DNA was derived from FFPE rectal cancer tissue and amplicons produced using the Cancer Hotspot Panel V2 and sequenced using semiconductor technology. NRAS mutations were observed at varying frequencies in the patient biopsy (12.2%) and all four subpopulations of cells in the resection with an average frequency of 7.3% (lowest 2.6%). The results of the NGS also provided the mutational status of 49 other genes that may have prognostic or predictive value, including KRAS and PIK3CA. NGS technology has been postulated in diagnostics because of its capability to generate results in large panels of clinically meaningful genes in a cost-effective manner. This case illustrates another potential advantage of this technology: its use for detecting low frequency mutations that may influence therapeutic decisions in cancer treatment.

Parallel Time Series Analysis and Income Inequality: A New Approach to Comparative Case Studies

This case study deals with the role of time series analysis in sociology, and its relationship with the wider literature and methodology of comparative case study research. Time series analysis is now well-represented in top-ranked sociology journals, often in the form of ‘pooled time series’ research designs. These studies typically pool multiple countries together into a pooled time series cross-section panel, in order to provide a larger sample for more robust and comprehensive analysis. This approach is well suited to exploring trans-national phenomena, and for elaborating useful macro-level theories specific to social structures, national policies, and long-term historical processes. It is less suited however, to understanding how these global social processes work in different countries. As such, the complexities of individual countries - which often display very different or contradictory dynamics than those suggested in pooled studies – are subsumed. Meanwhile, a robust literature on comparative case-based methods exists in the social sciences, where researchers focus on differences between cases, and the complex ways in which they co-evolve or diverge over time. A good example of this is the inequality literature, where although panel studies suggest a general trend of rising inequality driven by the weakening power of labour, marketisation of welfare, and the rising power of capital, some countries have still managed to remain resilient. This case study takes a closer look at what can be learned by applying the insights of case-based comparative research to the method of time series analysis. Taking international income inequality as its point of departure, it argues that we have much to learn about the viability of different combinations of policy options by examining how they work in different countries over time. By taking representative cases from different welfare systems (liberal, social democratic, corporatist, or antipodean), we can better sharpen our theories of how policies can be more specifically engineered to offset rising inequality. This involves a fundamental realignment of the strategy of time series analysis, grounding it instead in a qualitative appreciation of the historical context of cases, as a basis for comparing effects between different countries.

Photon nanojet lens: Design, fabrication and characterization

In this paper, a novel nanolens with super resolution, based on the photon nanojet effect through dielectric nanostructures in visible wavelengths, is proposed. The nanolens is made from plastic SU-8, consisting of parallel semi-cylinders in an array. This paper focuses on the lens designed by numerical simulation with the finite-difference time domain method and nanofabrication of the lens by grayscale electron beam lithography combined with a casting/bonding/lift-off transfer process. Monte Carlo simulation for injected charge distribution and development modeling was applied to define the resultant 3D profile in PMMA as the template for the lens shape. After the casting/bonding/lift-off process, the fabricated nanolens in SU-8 has the desired lens shape, very close to that of PMMA, indicating that the pattern transfer process developed in this work can be reliably applied not only for the fabrication of the lens but also for other 3D nanopatterns in general. The light distribution through the lens near its surface was initially characterized by a scanning near-field optical microscope, showing a well defined focusing image of designed grating lines. Such focusing function supports the great prospects of developing a novel nanolithography based on the photon nanojet effect.

Energy Optimization of Memory Intensive Parallel Workloads

Energy consumption is an important concern in modern multicore processors. The energy consumed by a multicore processor during the execution of an application can be minimized by tuning the hardware state utilizing knobs such as frequency, voltage etc. The existing theoretical work on energy minimization using Global DVFS (Dynamic Voltage and Frequency Scaling), despite being thorough, ignores the time and the energy consumed by the CPU on memory accesses and the dynamic energy consumed by the idle cores. This article presents an analytical energy-performance model for parallel workloads that accounts for the time and the energy consumed by the CPU chip on memory accesses in addition to the time and energy consumed by the CPU on CPU instructions. In addition, the model we present also accounts for the dynamic energy consumed by the idle cores. The existing work on global DVFS for parallel workloads shows that using a single frequency for the entire duration of a parallel application is not energy optimal and that varying the frequency according to the changes in the parallelism of the workload can save energy. We present an analytical framework around our energy-performance model to predict the operating frequencies (that depend upon the amount of parallelism) for global DVFS that minimize the overall CPU energy consumption. We show how the optimal frequencies in our model differ from the optimal frequencies in a model that does not account for memory accesses. We further show how the memory intensity of an application affects the optimal frequencies.

Development of numerical methodologies for parameter identification and shape optimization in metal forming simulations

Por parte da indústria de estampagem tem-se verificado um interesse crescente em simulações numéricas de processos de conformação de chapa, incluindo também métodos de engenharia inversa. Este facto ocorre principalmente porque as técnicas de tentativa-erro, muito usadas no passado, não são mais competitivas a nível económico. O uso de códigos de simulação é, atualmente, uma prática corrente em ambiente industrial, pois os resultados tipicamente obtidos através de códigos com base no Método dos Elementos Finitos (MEF) são bem aceites pelas comunidades industriais e científicas Na tentativa de obter campos de tensão e de deformação precisos, uma análise eficiente com o MEF necessita de dados de entrada corretos, como geometrias, malhas, leis de comportamento não-lineares, carregamentos, leis de atrito, etc.. Com o objetivo de ultrapassar estas dificuldades podem ser considerados os problemas inversos. No trabalho apresentado, os seguintes problemas inversos, em Mecânica computacional, são apresentados e analisados: (i) problemas de identificação de parâmetros, que se referem à determinação de parâmetros de entrada que serão posteriormente usados em modelos constitutivos nas simulações numéricas e (ii) problemas de definição geométrica inicial de chapas e ferramentas, nos quais o objetivo é determinar a forma inicial de uma chapa ou de uma ferramenta tendo em vista a obtenção de uma determinada geometria após um processo de conformação. São introduzidas e implementadas novas estratégias de otimização, as quais conduzem a parâmetros de modelos constitutivos mais precisos. O objetivo destas estratégias é tirar vantagem das potencialidades de cada algoritmo e melhorar a eficiência geral dos métodos clássicos de otimização, os quais são baseados em processos de apenas um estágio. Algoritmos determinísticos, algoritmos inspirados em processos evolucionários ou mesmo a combinação destes dois são usados nas estratégias propostas. Estratégias de cascata, paralelas e híbridas são apresentadas em detalhe, sendo que as estratégias híbridas consistem na combinação de estratégias em cascata e paralelas. São apresentados e analisados dois métodos distintos para a avaliação da função objetivo em processos de identificação de parâmetros. Os métodos considerados são uma análise com um ponto único ou uma análise com elementos finitos. A avaliação com base num único ponto caracteriza uma quantidade infinitesimal de material sujeito a uma determinada história de deformação. Por outro lado, na análise através de elementos finitos, o modelo constitutivo é implementado e considerado para cada ponto de integração. Problemas inversos são apresentados e descritos, como por exemplo, a definição geométrica de chapas e ferramentas. Considerando o caso da otimização da forma inicial de uma chapa metálica a definição da forma inicial de uma chapa para a conformação de um elemento de cárter é considerado como problema em estudo. Ainda neste âmbito, um estudo sobre a influência da definição geométrica inicial da chapa no processo de otimização é efetuado. Este estudo é realizado considerando a formulação de NURBS na definição da face superior da chapa metálica, face cuja geometria será alterada durante o processo de conformação plástica. No caso dos processos de otimização de ferramentas, um processo de forjamento a dois estágios é apresentado. Com o objetivo de obter um cilindro perfeito após o forjamento, dois métodos distintos são considerados. No primeiro, a forma inicial do cilindro é otimizada e no outro a forma da ferramenta do primeiro estágio de conformação é otimizada. Para parametrizar a superfície livre do cilindro são utilizados diferentes métodos. Para a definição da ferramenta são também utilizados diferentes parametrizações. As estratégias de otimização propostas neste trabalho resolvem eficientemente problemas de otimização para a indústria de conformação metálica.

Adaptive generalized predictive control algorithm implemented over an heterogeneous parallel architecture

In this paper a parallel implementation of an Adaprtive Generalized Predictive Control (AGPC) algorithm is presented. Since the AGPC algorithm needs to be fed with knowledge of the plant transfer function, the parallelization of a standard Recursive Least Squares (RLS) estimator and a GPC predictor is discussed here.