Subsystem Structure Research Articles

The Real-Time Integrated Information Management System for Building Construction

A real-time information management system for building construction (RIMBC), which is supported by the network technology, geographical information technology and office automation technology, is designed. This management system integrated the design data, survey data and test data can be used for the real-time search, management and update of design, survey documents by technical sections of functional departments in the field of construction engineering. This study gives a comprehensive and detailed depiction for the logical structure, entity structure, system process planning, database structure, subsystem structure and personnel training of RIMBC.

Real-time hybrid simulation approach for performance validation of structural active control systems: a linear motor actuator based active mass driver case study

SUMMARY Small-scale models have been commonly utilized in testing of performance of active mass driver (AMD) control systems. The utmost reason is that physical testing of AMD system at full scale is usually too expensive to afford, as well as hard to implement on site. With reference to the real-time hybrid simulation technology, a real-time AMD subsystem testing method is proposed in this paper. In this method, the entire system is composed of AMD as physical subsystem and target structure as numerical subsystem. The physical test is conducted on AMD subsystem, whereas the numerical simulation is carried out on the structure subsystem. Meanwhile, the real-time data are being communicated between these two subsystems. This method is then applied to the performance validation of a novel AMD control system, which is driven by a linear motor. In the test, a benchmark three-storey frame structure is employed as the numerical subsystem, and earthquake excitations are used as the external input. On the basis of a series of tests, both the time history and the statistical criteria show that the results of AMD subsystem and structure subsystem obtained in the real-time AMD subsystem test agree well with the simulation results. Furthermore, all the test results show good repeatability. Therefore, the feasibility and reliability of the proposed real-time AMD subsystem testing approach for performance validation of AMD subsystem has been demonstrated. Such kind of experimental method is efficient in terms of reducing cost associated with performance validation of large-scale active control systems prior to the implementation. Copyright © 2013 John Wiley & Sons, Ltd.

Applications of Statistical Energy Analysis in Influencing Factors Analysis of Aircraft Vibro-Acoustic Response Characteristics

The SEA model of hypersonic aircraft is established based on statistical energy analysis (SEA) theory. Three parameters of the SEA model are established by the theory and experiential formula. According to damping loss factors of model subsystem and acoustic absorptivity of cavity, sensitivity analysis of vibro-acoustic response is discussed. The effect that division way of plate subsystem and material structure cause to vibro-acoustic response is analyzed. The analysis results show that the material structure, damping loss factors and material type have the great effect on the characteristics of vibro-acoustic response. The division way of plate subsystem can affect computational accuracy greatly. The influencing factors should be synthetically considered in the design of acoustics structure.

Comparison of MDO Methods for an Earth Observation Satellite

It is shown in this paper the application of several multidisciplinary design optimization (MDO) methods for an earth observation satellite to optimize the performance of the earth observation. Based on the best earth observation criteria, a mathematical model of the satellite is proposed, which involves design variables, coupling variables and constraint functions. The analysis models of each subsystem are given, including the payload, attitude control, propulsion, power, and structure subsystem. The optimization is conducted by utilizing three MDO methods. Moreover the comparison among these methods is given to show the different features of these methods.

Multisensor Fault Identification Scheme Based on Decentralized Sliding Mode Observers Applied to Reconfigurable Manipulators

This paper concerns with a fault identification scheme in a class of nonlinear interconnected systems. The decentralized sliding mode observer is recruited for the investigation of position sensor fault or velocity sensor fault. First, a decentralized neural network controller is proposed for the system under fault-free state. The diffeomorphism theory is utilized to construct a nonlinear transformation for subsystem structure. A simple filter is implemented to convert the sensor fault into pseudo-actuator fault scenario. The decentralized sliding mode observer is then presented for multisensor fault identification of reconfigurable manipulators based on Lyapunov stable theory. Finally, two 2-DOF reconfigurable manipulators with different configurations are employed to verify the effectiveness of the proposed scheme in numerical simulation. The results demonstrate that one joint’s fault does not affect other joints and the sensor fault can be identified precisely by the proposed decentralized sliding mode observer.

Multidisciplinary Collaborative Optimization of General Parameters of Low Orbit Spacecraft

This article takes the optimization of general parameters of low-orbit spacecraft as object. Three subsystems of attitude and orbit control subsystem, power subsystem and structure subsystem were researched. Coupling relations between subsystems and system were described. Analysis models of the subsystems were provided. Meanwhile, optimization models of the researched problem were established based on collaborative optimization (CO). Sequential quadratic programming (NLPQL) was selected as search strategy of CO subsystem optimizer. While NLPQL, adaptive simulated annealing algorithm (ASA) and multi-island genetic algorithm (MIGA) were respectively selected as the search strategy of CO system-level optimizer to search. Furthermore, multidisciplinary feasible method (MDF) was used to optimize the same problem. NLPQL, ASA, MIGA were respectively selected as the search strategy of MDF system-level optimizer. The optimization result of CO was compared to the optimization result of MDF shows that using CO can get the result which close to the optimal result. That proves CO can be effectively applied to multidisciplinary design optimization of the general parameters of the low-orbit spacecraft.

Climate Change Subsystem Structure and Change: Network Mapping, Density and Centrality

Policy capacity in web-based settings is largely the
 product of nodality, which provides centralized actors with
 enhanced opportunities to detect information and affect
 behavior. This paper examines four Canadian virtual policy
 networks (VPN) currently facing policy challenges associated
 with climate change adaptation including finance, infrastructure,
 transportation, and forestry. The four sectors each
 face specific types of challenges that will presumably influence
 government’s policy capacity to respond to climate
 change adaptation, which in turn will affect the state’s nodal
 positioning in the VPNs. At the macro level governing capacity
 will vary considerably among these sectors with some
 more able to affect social behavior and evidence-informed
 learning, while others will struggle to lead policy discourse
 and development. It is hypothesized that the Canadian federal
 government’s nodality, which is shaped by both reputational
 capital and information credibility, will also be influenced
 by the nature of actors involved and the degree to
 which the VPN is internationalized.

Multiobjective optimization applied to structural sizing of low cost university-class microsatellite projects

In recent years, there has been continuing interest in the participation of university research groups in space technology studies by means of their own microsatellites. The involvement in such projects has some inherent challenges, such as limited budget and facilities. Also, due to the fact that the main objective of these projects is for educational purposes, usually there are uncertainties regarding their in orbit mission and scientific payloads at the early phases of the project. On the other hand, there are predetermined limitations for their mass and volume budgets owing to the fact that most of them are launched as an auxiliary payload in which the launch cost is reduced considerably. The satellite structure subsystem is the one which is most affected by the launcher constraints. This can affect different aspects, including dimensions, strength and frequency requirements. In this paper, the main focus is on developing a structural design sizing tool containing not only the primary structures properties as variables but also the system level variables such as payload mass budget and satellite total mass and dimensions. This approach enables the design team to obtain better insight into the design in an extended design envelope. The structural design sizing tool is based on analytical structural design formulas and appropriate assumptions including both static and dynamic models of the satellite. Finally, a Genetic Algorithm (GA) multiobjective optimization is applied to the design space. The result is a Pareto-optimal based on two objectives, minimum satellite total mass and maximum payload mass budget, which gives a useful insight to the design team at the early phases of the design.

Study of Bridge Health Monitoring Scheme Based on GPS Multi-Antenna Technique

Ongoing bridge collapse in both at home and abroad, makes people pay increasingly attention to bridge health monitoring. Bridge health monitoring which based on the GPS multiple antenna technology, GPRS wireless communications technology and so on, warning systems including GPS deformation monitoring subsystem, multiple antennas and safety assessment subsystem structure, can achieve bridge deformation data automatic acquisition, processing, analysis and structural safety evaluation and Internet remote transmission, automatic alarm function. Compared with the traditional method, the system has high accuracy and good data continuity, convenient operation, less investment etc, also has good social and economic benefits and broad application prospect.

Can innovation network projects result in efficient performance?

This paper examines the effects that process, structure and governance dimensions of networks have on innovation performance. The main focus of the paper is the multidimensional aspect of innovation networks and how these dimensions affect network performance. Technology management, resource-based, transaction costs and social capital perspectives are applied in the construction of the model variables of each subsystem or dimension analyzed. With results drawn from a sample of 350 project managers identified in the European Union CORDIS database who are actively involved in European innovation networks, we argue that the performance of innovation networks is increased through the suitable design of process, structure and governance subsystems. Empirical findings also show that interactions between these subsystems have a complementary or synergic effect resulting in improved innovation performance.

Role of Knowledge Management Initiatives in Organizational Innovativeness: Empirical Findings from the IT Industry

This paper addresses the relationship between knowledge management initiatives in Indian IT organizations and their innovativeness at the organization level by using the survey research methodology. Knowledge management initiatives were measured in the context of cultural, structural, and technological interventions. Innovation was measured in terms of organizational behaviour related to sensitivity, learning, newness, trialability, communicability, risk-readiness, and absorption. A conceptual model was developed to assess the relationship between knowledge management initiatives and innovativeness. A hypothesis that knowledge management initiatives (KMI) influence the innovativeness of the organization was propounded. The questionnaire developed to assess knowledge management initiatives had 60 items, while an already available questionnaire consisting of 65 items was used to measure innovativeness. Eventually, the number of items in the knowledge management initiatives and innovativeness questionnaires was bought down to 45 and 34 respectively. Items were measured on a fivepoint Likert type rating scale, ranging from strongly agree to strongly disagree. The reliability of the questionnaires was checked using Cronbach Alpha. The study was carried out on 84 professionals from 20 Bangalore-based IT organizations that had implemented knowledge management initiatives and had SEI CMM level 5. Means and standard deviations of the variables were computed. The variables were subjected to correlation analysis and factor analysis. A multiple regression analysis was done to identify the influence of knowledge management initiatives on organizational innovativeness. An organizational innovativeness score, was used as the dependent variable and the variables of knowledge management initiatives were used as the independent variables. The results of data analysis showed that the initiatives taken by companies to enhance their knowledge assets fall into the culture, structure, and technology subsystems and that all the three are highly correlated: Technology and culture are more strongly associated with each other, as compared to their association with structure. All the three KMI variables strongly influence organizational innovativeness, with ‘culture’ being the most important. ‘Learning climate,’ a variable of culture, is found to be the most significant of the variables to influence innovativeness. Hence, organizations that lay emphasis on learning and provide excellent training facilities can foster a more innovative environment. Interestingly, ‘risk readiness‘ is not a factor contributing to innovativeness and is not significantly associated with the other variables. The variables like leadership, networking, reward and recognition, structure and technology do not significantly influence innovativeness.

Structure and elastic properties ofMg(OH)2 from density functional theory

The structure, lattice dynamics and mechanical properties of magnesium hydroxide havebeen investigated by static density functional theory calculations as well as ab initiomolecular dynamics. The hypothesis of a superstructure existing in the lattice formed bythe hydrogen atoms has been tested. The elastic constants of the material havebeen calculated with a static deformations approach and are in fair agreementwith the experimental data. The hydrogen subsystem structure exhibits signs ofdisordered behaviour while maintaining correlations between the angular positions ofneighbouring atoms. We establish that the essential angular correlations betweenhydrogen positions are maintained to a temperature of at least 150 K and that theyare well described by a physically motivated probabilistic model. The rotationaldegree of freedom appears to be decoupled from the lattice directions above 30 K.

Managing Cooperation Programs in Developing Countries: A Case Comparative Analysis in Kenya, Pakistan, Brazil, Somalia, and Egypt

Cooperation programs contribute significantly to the delivery of social, health, and infrastructure policies in developing countries, but relatively little empirical work has been made on how they are managed. This paper aims to contribute filling this gap through a case comparative analysis of the implementation of cooperation programs conducted by Italy in Kenya, Pakistan, Brazil, Somalia, and Egypt. The analysis of the cases provides evidence for explanatory research arguments which hold that cooperation programs' management practices can be affected by the developing countries' administrative system, the foreign aid policy subsystem's structure, and the cultural and social environment. These findings suggest that context features need to be taken into account to qualify extant generalizing arguments about the role played by incentives on the behavior of donor agencies and principal recipients of foreign aid programs.

An investigation of Interface-GMRES(R) for fluid–structure interaction problems with flutter and divergence

The basic subiteration method for solving fluid---structure interaction problems consists of an iterative process in which the fluid and structure subsystems are alternatingly solved, subject to complementary partitions of the interface conditions. The main advantages of the subiteration method are its conceptual simplicity and its modularity. The method has several deficiencies, however, including a lack of robustness and efficiency. To bypass these deficiencies while retaining the main advantages of the method, we recently proposed the Interface-GMRES(R) solution method, which is based on the combination of subiteration with a Newton---Krylov approach, in which the Krylov space is restricted to the interface degrees-of-freedom. In the present work, we investigate the properties of the Interface-GMRES(R) method for two distinct fluid---structure interaction problems with parameter-dependent stability behaviour, viz., the beam problem and the string problem. The results demonstrate the efficiency and robustness of the Interface-GMRES(R) method.

On the adjoint-consistent formulation of interface conditions in goal-oriented error estimation and adaptivity for fluid–structure interaction

The numerical solution of fluid–structure-interaction problems poses a paradox in that most of the computational resources are consumed by the subsystem of least practical interest, viz., the fluid. Goal-oriented adaptive discretization methods provide a paradigm to bypass this paradox. Based on the solution of a dual problem, the contribution of local residuals to the error in a specific goal functional is estimated, and only the regions that yield a dominant contribution are refined. In the present work, we address a fundamental complication in the application of goal-oriented adaptivity to fluid–structure-interaction problems, namely, that the treatment of the interface conditions has nontrivial consequences for the properties of the dual problem. In the context of a linearized model problem, we consider two equivalent discretizations differing only on the formulation of the interface coupling terms. By means of an adjoint consistency analysis, we show that only one of these discretizations is adjoint consistent. Numerical experiments convey that the two discretizations behave very differently for the dual problem, and that the adjoint-consistent discretization yields more reliable error estimates. Based on the adjoint-consistent discretization, we finally present some h- and hp-adaptive results, confirming that tremendous savings in computational cost can be realized through the use of goal-oriented refinement strategies. The numerical experiments illustrate that the goal-oriented approach effectively equilibrates the error contributions of the fluid and structure subsystems, which is imperative for efficiently resolving the coupled fluid–structure-interaction problem, and which cannot be accomplished by uniform or residual-based refinement strategies.

A decision-making module for aiding ship system automation design: A knowledge-based approach

The use of elements of artificial intelligence, including knowledge-based systems, becomes more and more widespread in aiding design problem solutions. The authors have been working on problems of control systems for many years. A design process involves many decision problems connected with, for example, a choice of a subsystem structure, subunits or particular elements selection. Because of such regards, it was decided to extend knowledge-based system with a module for support of such decision making.In this paper, an elaborated module for decision-making support is considered. The basic theoretical assumptions concerning the accepted method of multiattribute decision making based on pairwise comparison in categories of hierarchical decision process (AHP) is presented. Accepted knowledge representation in AHP method and pairwise comparison method and methods of expert knowledge acquisition are discussed. The module functioning is illustrated by an example of choice of temperature sensors in a system of fuel transport to Diesel engine of a main propulsion unit of a ship.

Neural representations and mechanisms for the performance of simple speech sequences.

Speakers plan the phonological content of their utterances before their release as speech motor acts. Using a finite alphabet of learned phonemes and a relatively small number of syllable structures, speakers are able to rapidly plan and produce arbitrary syllable sequences that fall within the rules of their language. The class of computational models of sequence planning and performance termed competitive queuing models have followed K. S. Lashley [The problem of serial order in behavior. In L. A. Jeffress (Ed.), Cerebral mechanisms in behavior (pp. 112-136). New York: Wiley, 1951] in assuming that inherently parallel neural representations underlie serial action, and this idea is increasingly supported by experimental evidence. In this article, we developed a neural model that extends the existing DIVA model of speech production in two complementary ways. The new model includes paired structure and content subsystems [cf. MacNeilage, P. F. The frame/content theory of evolution of speech production. Behavioral and Brain Sciences, 21, 499-511, 1998 ] that provide parallel representations of a forthcoming speech plan as well as mechanisms for interfacing these phonological planning representations with learned sensorimotor programs to enable stepping through multisyllabic speech plans. On the basis of previous reports, the model's components are hypothesized to be localized to specific cortical and subcortical structures, including the left inferior frontal sulcus, the medial premotor cortex, the basal ganglia, and the thalamus. The new model, called gradient order DIVA, thus fills a void in current speech research by providing formal mechanistic hypotheses about both phonological and phonetic processes that are grounded by neuroanatomy and physiology. This framework also generates predictions that can be tested in future neuroimaging and clinical case studies.

Designing Distributed Diagnosers for Complex Continuous Systems

Wear and tear from sustained operations cause systems to degrade and develop faults. Online fault diagnosis schemes are necessary to ensure safe operation and avoid catastrophic situations, but centralized diagnosis approaches have large memory and communication requirements, scale poorly, and create single points of failure. To overcome these problems, we propose an online, distributed, model-based diagnosis scheme for isolating abrupt faults in large continuous systems. This paper presents two algorithms for designing the local diagnosers and analyzes their time and space complexity. The first algorithm assumes the subsystem structure is known and constructs a local diagnoser for each subsystem. The second algorithm creates the partition structure and local diagnosers simultaneously. We demonstrate the effectiveness of our approach by applying it to the Advanced Water Recovery System developed at the NASA Johnson Space Center.

Interpolatory projection methods for structure-preserving model reduction

We present a framework for interpolatory model reduction that treats systems having a generalized coprime factorization C ( s ) ▪ ( s ) − 1 B ( s ) + D . This includes rational Krylov-based interpolation methods as a special case. The broader framework allows retention of special structure in reduced models such as symmetry, second- and higher order structure, state constraints, internal delays, and infinite dimensional subsystems. Two numerical examples are provided for systems associated with viscoelastic dynamics and with an internal state delay that demonstrate the effectiveness and flexibility of the approach.

Treatment of acoustic fluid–structure interaction by localized Lagrange multipliers: Formulation

A new concept is presented for modeling the dynamic interaction between an acoustic fluid and an elastic structure. The coupling of this multiphysics system is done by inserting a kinematic interface frame between the fluid and the structure, and using node-collocated Lagrange multipliers to connect the frame to each subsystem. The time-domain response analysis is performed by a partitioned analysis procedure. The main advantages of this localized Lagrange multiplier (LLM) primal-dual coupling method are: complete localization of the structure and fluid subsystems, elimination of the conventional predictor in the partitioned time integration method, and the ability to accommodate non-matching meshes. The standard Newmark time integrator is used on both the fluid and structure models. It is shown that if the integrator is A-stable and second-order accurate for a monolithic treatment, it retains those properties for both Mortar and LLM partitioned solution procedures. Infinite and finite piston problems are used to explain and verify the methodology. A sequel paper under preparation presents and discusses a set of benchmark and application examples that involve the response of existing dams to seismic excitation.