Dual Faces Architecture of Nias

Many Indonesian people built a traditional house based on beliefs of their ancestors for generations, without knowing the scientific reason. Meanwhile, indirectly, ancestors already thinking about housing that adapts the environmental conditions such as in Nias Island. Nias is an island that has two different forms of traditional houses which are affected by the differences geographic, highland and lowland. Geographic factors and beliefs not only affect the shape of the house but also the structure of the house. Located on the earthquake fault lines, Nias traditional houses was designed to withstand earthquakes that often befall. A study using description and analysis methods about design and structure which used in traditional houses in Nias Island, would develop a good sense of the idea to apply these materials on modern building to preserve the culture of Indonesia

Autoregressive modelling for rolling element bearing fault diagnosis

In this study, time series analysis and pattern recognition analysis are used effectively for the purposes of rolling bearing fault diagnosis. The main part of the suggested methodology is the autoregressive (AR) modelling of the measured vibration signals. This study suggests the use of a linear AR model applied to the signals after they are stationarized. The obtained coefficients of the AR model are further used to form pattern vectors which are in turn subjected to pattern recognition for differentiating among different faults and different fault sizes. This study explores the behavior of the AR coefficients and their changes with the introduction and the growth of different faults. The idea is to gain more understanding about the process of AR modelling for roller element bearing signatures and the relation of the coefficients to the vibratory behavior of the bearings and their condition

Subcube embeddability and fault tolerance of augmented hypercubes

Hypercube networks have received much attention from both parallel processing and communications areas over the years since they offer a rich interconnection structure with high bandwidth, logarithmic diameter, and high degree of fault tolerance. They are easily partitionable and exhibit a high degree of fault tolerance. Fault-tolerance in hypercube and hypercube-based networks received the attention of several researchers in recent years; The primary idea of this study is to address and analyze the reliability issues in hypercube networks. It is well known that the hypercube can be augmented with one dimension to replace any of the existing dimensions should any dimension fail. In this research, it is shown that it is possible to add i dimensions to the standard hypercube, Qn to tolerate (i - 1) dimension failures, where 0 \u3c i ≤ n. An augmented hypercube, Qn +(n) with n additional dimensions is introduced and compared with two other hypercube networks with the same amount of redundancy. Reliability analysis for the three hypercube networks is done using the combinatorial and Markov modeling. The MTTF values are calculated and compared for all three networks. Comparison between similar size hypercube networks show that the augmented hypercube is more robust than the standard hypercube; As a related problem, we also look at the subcube embeddability. Subcube embeddability of the hypercube can be enhanced by introducing an additional dimension. A set of new dimensions, characterized by the Hamming distance between the pairs of nodes it connects, is introduced using a measure defined as the magnitude of a dimension. An enumeration of subcubes of various sizes is presented for a dimension parameterized by its magnitude. It is shown that the maximum number of subcubes for a Qn can only be attained when the magnitude of dimension is n - 1 or n. It is further shown that the latter two dimensions can optimally increase the number of subcubes among all possible choices

Knowledge From Pictures (KFP)

The old maxim goes: 'A picture is worth a thousand words'. The objective of the research reported in this paper is to demonstrate this idea as it relates to the knowledge acquisition process and the automated development of an expert system's rule base. A prototype tool, the Knowledge From Pictures (KFP) tool, has been developed which configures an expert system's rule base by an automated analysis of and reasoning about a 'picture', i.e., a graphical representation of some target system to be supported by the diagnostic capabilities of the expert system under development. This rule base, when refined, could then be used by the expert system for target system monitoring and fault analysis in an operational setting. Most people, when faced with the problem of understanding the behavior of a complicated system, resort to the use of some picture or graphical representation of the system as an aid in thinking about it. This depiction provides a means of helping the individual to visualize the bahavior and dynamics of the system under study. An analysis of the picture augmented with the individual's background information, allows the problem solver to codify knowledge about the system. This knowledge can, in turn, be used to develop computer programs to automatically monitor the system's performance. The approach taken is this research was to mimic this knowledge acquisition paradigm. A prototype tool was developed which provides the user: (1) a mechanism for graphically representing sample system-configurations appropriate for the domain, and (2) a linguistic device for annotating the graphical representation with the behaviors and mutual influences of the components depicted in the graphic. The KFP tool, reasoning from the graphical depiction along with user-supplied annotations of component behaviors and inter-component influences, generates a rule base that could be used in automating the fault detection, isolation, and repair of the system

Seismic protection of cable-stayed bridges applying fluid viscous dampers

The present work constitutes an approach to the seismic protection of cable-stayed bridges including the incorporation of fluid viscous dampers as additional energy dissipation devices. The idea of the authors is to provide an up-to-date vision of the problem taking into account that long-period structures such as those proposed here, need to be adequately protected against strong motions, and considering that, because of their importance, an elastic behaviour is desirable. Chapter 1 describes the object to study ingeneral terms. Chapter 2 constitutes a state-of-the-art review regarding the seismic behaviour and performance of fluid viscous dampers as external energy dissipation devices. The mechanical behaviour and technological aspects are now introduced with an energetic point of view, in which some practical applications are exposed and discussed. Chapter 3 describes the seismic response of cable-stayed bridges without external seismic protection, considering a parametric analysis in order to study the effects of the stay cable layout, stay spacing and deck level. A complete modal characterization is exposed, followed by a response spectrum analysis for comparative purposes. The effect of variations of the stay forces is analyzed, and finally, a nonlinear step-by-step analysis is performed for the critical structures, considering the velocity dependence of such bridges and the effects of far-fault and near-fault ground motions. The last Chapter exposes the seismic analysis of the selected structures including the incorporation of fluid viscous dampers as passive additional energy dissipation devices. Because of the inherent nonlinear behaviour of the structures and external devices, a mandatory nonlinear direct integration time-history analysis is performed for all the cases, in which parametric analyses are carried out in order to select the best damper parameters, and for the case of both far-fault and near-fault ground motions. In this part, comparative results are exposed with the aim to propose some practical recommendations.Postprint (published version

Resilience and risk analysis of fault-tolerant control design in continuous pharmaceutical manufacturing

PresentationThe effects of the paradigm shift from batch to continuous manufacturing on pharmaceutical industry, in terms of process safety and product quality, e.g., danger of dust explosions and risk of off-spec products, are of major concerns in the recent research progress in control system design. Specifically, a fault-tolerant control of critical process parameters (CPPs) and critical quality attributes (CQAs) is of paramount importance for the continuous operation with built-in safety and quality. In this study, a systematic framework for fault-tolerant control design, analysis, and evaluation for continuous pharmaceutical solid-dosage manufacturing is proposed, consisting of system identification, control design and analysis (controllability, stability, resilience, etc.), hierarchical three-layer control structures (model predictive control, state estimation, data reconciliation, etc.), risk mapping, assessment and planning (Risk MAP) strategies, and control performance evaluation. The key idea of the proposed framework is to identify the potential risks in the control design, material variance, and process uncertainties, under which the control strategies are evaluated. The framework is applied to a continuous direct compaction process, specifically the feeding-blending system wherein the major source of variance in the process operation and product quality arises. It can be demonstrated that the process operation failures and product quality variances in the feeding-blending system can be mitigated and managed through the proposed systematic fault-tolerant control system design and risk analysis framework

Hierarchical Simulation to Assess Hardware and Software Dependability

This thesis presents a method for conducting hierarchical simulations to assess system hardware and software dependability. The method is intended to model embedded microprocessor systems. A key contribution of the thesis is the idea of using fault dictionaries to propagate fault effects upward from the level of abstraction where a fault model is assumed to the system level where the ultimate impact of the fault is observed. A second important contribution is the analysis of the software behavior under faults as well as the hardware behavior. The simulation method is demonstrated and validated in four case studies analyzing Myrinet, a commercial, high-speed networking system. One key result from the case studies shows that the simulation method predicts the same fault impact 87.5% of the time as is obtained by similar fault injections into a real Myrinet system. Reasons for the remaining discrepancy are examined in the thesis. A second key result shows the reduction in the number of simulations needed due to the fault dictionary method. In one case study, 500 faults were injected at the chip level, but only 255 propagated to the system level. Of these 255 faults, 110 shared identical fault dictionary entries at the system level and so did not need to be resimulated. The necessary number of system-level simulations was therefore reduced from 500 to 145. Finally, the case studies show how the simulation method can be used to improve the dependability of the target system. The simulation analysis was used to add recovery to the target software for the most common fault propagation mechanisms that would cause the software to hang. After the modification, the number of hangs was reduced by 60% for fault injections into the real system

Pseudo-sample based contribution plots: innovative tools for fault diagnosis in kernel-based batch process monitoring

[EN] This article explores the potential of kernel-based methods for fault diagnosis in batch process monitoring by combining Kernel-Principal Component Analysis and three common techniques which permit analyzing batch data by means of bilinear models: variable-wise unfolding, batch-wise unfolding and landmark feature extraction. Gower's idea of pseudo-sample projection is exploited to develop novel tools, the pseudo-sample based contribution plots, for diagnostic purposes. The results show that, when the datasets under study are affected by severe non-linearities, the proposed approach performs better than classical ones.This research work was partially supported by the Spanish Ministry of Economy and Competitiveness under the project DPI2011-28112-C04-02 and Shell Global Solutions International B.V. (Amsterdam, The Netherlands) under the project PT13698.Vitale, R.; Noord, OED.; Ferrer Riquelme, AJ. (2015). Pseudo-sample based contribution plots: innovative tools for fault diagnosis in kernel-based batch process monitoring. Chemometrics and Intelligent Laboratory Systems. 149:40-52. https://doi.org/10.1016/j.chemolab.2015.09.013S405214