Structure Of Intelligent System Research Articles

Applications of Smart Material to Enhance Daylighting as a tool to Improve Sustainability of Atriums

Applications for smart building materials include making them more environmentally friendly, better able to suit user needs, and less likely to cause environmental issues. This kind of material has been suggested recently, following great scientific advancements and novel sustainable architecture techniques, as smart materials that allow controlled transmission of light and heat into the building and remove some of the traditional limitations in window application, smart material technologies are key feature competitiveness of the twenty-first century. Modern construction materials are capable of achieving great levels of utility, “Smart materials” will play a crucial role in building technology development; These materials that are part of an intelligent structural system, have the ability to sense its environment, so smart materials can function like living systems, An important element of an architectural design strategy that is environmentally sustainable is the use of daylight as part of an integrated, controlled lighting strategy. For well-designed structures, the atrium could be a significant source of daylight. It also offers other environmental advantages such as solar energy gain, reduced energy loss, and natural ventilation. The major elements of the atrium for the daylight design are a system of skylights and windows to provide daylight levels in the spaces adjacent to the atrium.

Numerical and random forest modelling of the impact response of hierarchical auxetic structures

Major sources of concern when auxetic protective structures are deployed in service of mission-critical applications encompass the triggering of high impact stress and the weakening of the structures’ elastic strength in response to the impact events. The current prevailing approach to assessing the impact resistance of these structures broadly hinges on mechanics-informed nonlinear finite element (FE) analysis. However, this method is computationally expensive and ill-suited for tackling the implementation of automated condition monitoring schemes. To address these issues, first, this paper proposes a hybrid hierarchical auxetic structure named Hybrid-Hierarchical Re-entrant Honeycomb (HHRH) that is endowed with impact stress-reducing capabilities. Next, using explicit FE, the investigation uncovers the interplay between the key geometric features of this HHRH auxetic structure and the impact performance under low, intermediate, and high crushing velocities. The outcome of the nonlinear explicit FE simulations is then unified with random forests (RF) scheme towards the establishment of intelligent auxetic structural systems. The results revealed that the developed HHRH maintained the auxeticity of the regular re-entrant auxetic and exhibited superior performance in some crushing strain regions. Moreover, the HHRH structure manifests up to an 85 % reduction in peak stress and the proposed reinforcement boosts the auxetic property by up to 23 % when compared to the regular re-entrant auxetic structure under high-velocity applications. Regarding the established data-driven RF-enabled machine learning model, its predictive strength with optimally-tuned hyperparameters is demonstrated to excellently capture the nonlinear multi-modal crushing stress response at various crushing strains, velocities, and geometric variations. Data AvailabilityThe raw/processed data required to reproduce these findings cannot be shared at this time as the data also forms part of an ongoing study.

Intelligent Planning of Tourist Routes Based on Cloud Computing and Marching Algorithm

In order to improve the effect of modern tourism route planning, this article combines the cloud computing advancement algorithm to construct a tourism route intelligent planning system and combines the current people's tourism needs to carry out intelligent tourism route planning. Based on the fast forward algorithm of the program function equation, this article uses the fast forward algorithm to solve the discrete nonlinear program function equation and directly obtain the cloud computing data. In addition, the self-intersection phenomenon of the wave front must be considered when describing the characteristics of the cloud computing information field by using the process of the equivalent cloud computing information front expanding to the surrounding. Finally, this article constructs the intelligent system structure. The research results show that the intelligent travel route planning system based on cloud computing and marching algorithm proposed in this article can play an important role in modern smart tourism.

Design of Hierarchical Retrieval Model of Digital English Teaching Information Based on Ontology

In order to improve the effect of English teaching information retrieval, this paper designs a hierarchical retrieval model of digital English teaching information through ontology and constructs an intelligent system structure that can be used for hierarchical retrieval of digital English teaching information. Moreover, this paper proposes a method for judging the similarity of English teaching information structure based on non-negative matrix factorization and develops a hierarchical retrieval model of digital English teaching information based on ontology according to an improved algorithm. In addition, this paper uses the hierarchical search idea to design the hierarchical structure and study the system framework and hierarchical process. Finally, this paper verifies the performance of the system through simulation experiments. The experiment shows that the hierarchical retrieval model of digital English teaching information based on ontology proposed in this paper meets the basic needs of this paper to build an English teaching information system and can play a certain role in English teaching.

Advances in intelligent long-term vibration-based structural health-monitoring systems for bridges

The true realization of the benefits of vibration based structural health monitoring (VBSHM) in real-world applications is acquired through long-term continuous monitoring so that one can attain a detailed grasp of the behavior of the monitored structure. The challenges in long-term continuous VBSHM include: the large volume of accumulated monitoring data; the effective extraction of engineering information amid the influences of noise and uncertainties embedded in the monitoring data; maintaining continuity and consistency in the long-term monitoring data considering that the system and instrumentation may change due to sensor failure or renewal due to advances in sensing technologies. To meet these challenges, this paper presents recent research that has resulted in the development of a framework and specialized signal processing and data analytic tools for long-term continuous VBSHM suitable for real-world monitoring applications of structures in the field. These include efficient tools for large scale intelligent data processing and analysis, management of monitoring database and extracted information relevant to the structural health of the monitored structure. The novel Automated In-Line Full Space Identification (AI-FSI) method is presented to address the needs and challenges associated with long-term continuous VBSHM, such as the automation of all data processing and analysis operations including modal parameter estimations and mode tracking, and the need of minimizing the measurement and computational uncertainties and variability in the operational modal analysis results. A smart self-diagnostic system for the monitoring of the health of the data collection sensors and monitoring system has also been developed that will allow the consistent use of the monitoring data of different sensor configurations and era in the monitoring project. Examples on the efficiency of analyzing the monitoring data collected over 20 years from the Confederation Bridge monitoring project in Atlantic Canada by using the developed novel framework and data analytic tools are presented.

Security-Aware Routing Protocol Based on Artificial Neural Network Algorithm and 6LoWPAN in the Internet of Things

Today, with increasing information technology such as the Internet of Things (IoT) in human life, interconnection and routing protocols need to find optimal solution for safe data transformation with various smart devices. Therefore, it is necessary to provide an enhanced solution to address routing issues with respect to new interconnection methodologies such as the 6LoWPAN protocol. The artificial neural network (ANN) is based on the structure of intelligent systems as a branch of machine interference, has shown magnificent results in previous studies to optimize security-aware routing protocols. In addition, IoT devices generate large amounts of data with variety and accuracy. Therefore, higher performance and better data handling can be achieved when this technology incorporates data for sending and receiving nodes in the environment. Therefore, this study presents a security-aware routing mechanism for IoT technologies. In addition, a comparative analysis of the relationship between previous approaches discusses with quality of service (QoS) factors such as throughput and accuracy for improving routing mechanism. Experimental results show that the use of time-division multiple access (TDMA) method to schedule the sending and receiving of data and the use of the 6LoWPAN protocol when routing the sending and receiving of data can carry out attacks with high accuracy.

Vibration suppression of wind turbine nacelle with active electromagnetic mass damper systems using adaptive backstepping control

Many structural systems, such as wind turbines, are exposed to high levels of stress during operation. This is mainly because of the flow-induced vibrations caused by the wind load encountered in every tall structure. Preventing the flow-induced vibration has been an important research area. In this study, an active electromagnetic mass damper system was used to eliminate the vibrations. The position of the stabilizer mass in the active electromagnetic mass damper system was determined according to the displacement information read on the system without using any spring element, unlike any conventional system. The proposed system in this study has a structure that can be implemented as a vibration suppressor in many intelligent structural systems. Two opposing electromagnets were used to determine the instant displacement of the stabilizer mass. The control currents to be given to these electromagnets are determined by using an adaptive backstepping control design. The adaptive controller algorithm can predict the wind load used in the controller design without prior knowledge of the actual wind load. It was observed that the designed active electromagnetic mass damper structure is successful in suppressing system vibrations. As a result, the proposed active electromagnetic mass damper system has been shown to be suitable for structural systems in flow-induced vibration damping.

Intelligent system construction as consequent transformation of the model range of its functional prototypes

Application of the technology of consecutive construction of the functionally expanding model range of structural system prototypes is an advanced conceptual development direction of intellectual systems construction methods. The guiding principle of intellectual system construction under the suggested technology is that a highly sophisticated system is worked out and adjusted by stages with the use of the structural increment and functional complexity parallel-sequential scheme. At every construction step it is implemented in the form of a hardware and software complex – the structural prototype with a certain set of allocated components and performed functions. The structural prototype is understood as a certain version of its construction in the form of a logical or physical model, which includes a predetermined set of information, technical and software tools, performs system functions, makes it possible to evaluate the achieved parameter levels, as well as ensures further system build-up and development. Verbal-heuristic and graphic-heuristic models, which reflect the set of original requirements and the intelligent system structure, are used as mandatory prototypes of primary levels. The mandatory prototype of subsequent levels of the system technology includes a material model of the system nucleus, which combines hardware and software components, where joint functioning delivers the required set of integrative systematic properties. Sequential step-by-step choice of all the more complex prototypes with simultaneous enrichment of the composition of applied tools and performed system functions forms the expanded model range of the system. In the practice of systems development it is limited with a certain upper level prototype, which meets preset technical requirements to the system. Step-by- step development and adjustment of models, which are highly complicated prototypes, with the use of the parallel-sequential scheme of their structural enrichment and functional complication, is the effective technological trend of co-engineering.

Research and Development of Civil Engineering Intelligent Structure System

With the rapid development of global civil engineering construction, the intelligent structural system of civil engineering has evolved into one of the current global frontier disciplines. The research on the intelligent structural system of civil engineering and the current development situation are analyzed, and the main problems are combined. Giving reasonable suggestions is of great significance to the country's vigorous development of civil engineering intelligent structure system. This paper designs a new type of three-dimensional fiber grating sensor, including the design of the matrix model and the design of fiber grating strain gauges. This new sensor can effectively measure three-dimensional space, greatly expanding the application range of fiber grating sensors. In this paper, the design lighting area of each light pipe is taken as a unit. Each unit is set with 4 measuring points at the center and the edge. Each measuring point reads 3 illuminance value parameters and records the average value. Based on the results and comprehensive consideration of the short board situation, the research conclusions and recommendations are put forward. The foundation wall with aerated concrete blocks as the wall material can meet the requirements of 50% energy saving for exterior wall buildings with external decoration and internal insulation mortar. Compared with the benchmark wall of 50% energy saving of external wall buildings, the heat transfer coefficient is reduced by 50.1%, and the actual energy-saving effect of the wall can reach 75%. Meet the requirements of 65% for the energy-saving effect of exterior wall buildings. This paper considers economic parameters, such as the investment cost of building insulation materials, energy-saving income, and investment recovery period, and establishes a calculation model for analyzing the economics of insulation materials. Based on the heat transfer model of the composite wall and the fuel energy combustion equation, greenhouse gas is an established calculation model for CO2 and SO2 emissions. Studies have shown that when considering the room temperature insulation performance of insulation materials, the time required for the side of the concrete slab with glass fiber felt and aerogel insulation materials is about 2022 and 3363 s, respectively, indicating the fire resistance of aerogel insulation materials significantly better than fiberglass.

Intelligent Cognitive Radio Ad-Hoc Network: Planning, Learning and Dynamic Configuration

Cognitive radio (CR) is an adaptive radio technology that can automatically detect available channels in a wireless spectrum and change transmission parameters to improve the radio operating behavior. A CR ad-hoc network (CRAHN) should be able to coexist with primary user (PU) systems and other CR secondary systems without causing harmful interference to licensed PUs as well as dynamically configure autonomous and decentralized networks. Therefore, an intelligent system structure is required for efficient spectrum use. In this paper, we present a learning-based distributed autonomous CRAHN network system model for network planning, learning, and dynamic configuration. Based on the system model, we propose machine learning-based optimization algorithms for spectrum sensing, cluster-based ad-hoc network configuration, and context-aware signal classification. Using the sensing engine and the cognitive engine, the surrounding spectrum usage and the neighbor network operation status can be analyzed. The proposed policy engine can create network operation policies for the dynamically changing surrounding wireless environment, detect policy conflicts, and infer the optimal policy for the current situation. The decision engine finally determines and configures the optimal CRAHN configuration parameters through cooperation with a learning engine, in which we implement the proposed machine-learning algorithms. The simulation results show that the proposed machine-learning CRAHN algorithms can construct CR cluster networks that have a long network lifetime and high spectrum utility. Additionally, with high signal context recognition performance, we can ensure coexistence with neighboring systems.

BIM based cyber-physical systems for intelligent disaster prevention

The cyber-physical systems (CPS) has emerged in the last decade and become one of the most cutting-edge research fields. CPS is a highly integrated system of communication, computing, and control strategies. Although CPS has been studied and applied in some fields such as intelligent transportation, intelligent manufacturing, intelligent buildings, and smart cities, there is a lack of research on CPS based intelligent disaster prevention and mitigation structural system. Because structural disaster prevention and reduction have their own characteristics, it is necessary to investigate CPS based technology and system for intelligent structural disaster prevention and reduction. In this paper, a preliminary study is conducted on cyber-physical based intelligent structural disaster prevention technologies and structural systems using the Building Information Model (BIM) platform. The proposed CPS consists of the multi-source data precision sensing and intelligent control technology in the physical subsystem/layer, reliable data transmission network in the communication subsystem/layer, and real-time identification algorithm of structural state and adaptive control strategy in the information subsystem/layer. Moreover, BIM platform and Internet of things (IoT) technology are adopted for constructing the cloud architecture of CPS to achieve a high degree of integration of monitoring, identification and control, and to improve the real-time and accurate intelligent monitoring of structural disaster prevention and mitigation.

Research and development of civil engineering intelligent structure system

<p>With the fast-paced development of China's economy, science and technology have made rapid progress, as well as the research on civil engineering construction. In particular, civil engineering intelligent structure system has evolved into one of the world's leading disciplines and is also the future development trend, attracting extensive attention and research from professionals in this field. This paper mainly analyzes the research and current development of civil engineering intelligent structure system, and gives reasonable suggestions based on the main problems, so as to provide some references for better development and progress of this technology.</p>

Study on the Intelligent Creel of Advanced Carpet Loom

The detailed design and development of the intelligent creel mechanical structure and control system is based on the research and analysis of specific operation and practical functions, which realizes its functions of intelligent analysis, right amount of supply and prompt storing. As the transmission of the carpet yarns from the storage unit to the loom, the intelligent creel is able to automatically make analysis of the usage amount of different yarns according to different orders, makes more reasonable supplies to the loom and prepares yarns before used up, which makes best use of the yarn and increases the production efficiency. Meanwhile, a lot of time and labor of replacing yarns is saved.

Design considerations and experimental studies on semi-active smart pin joint

Hostile dynamic loadings such as severe wind storms, earthquakes, and sudden impacts can cause severe damage to many civil engineering structures. An intelligent structural system equipped with smart structural members that are controllable in real-time is an effective solution to structural damage and failure during such situations. Civil intelligent structures with controllable properties to adapt to any changes due to dynamic loadings can lead to effective protection of structures and their occupants. In this paper, design and testing of a semi-active magnetorheological (MR) pin joint, in which the moment resistance can be controlled in real-time by altering the magnetic field, is reported with the view of using it as a potential candidate for smart members in the development of intelligent structures. Design of prototype smart pin joints includes theoretical analysis related to the radius of the rotary plate, the property of MR fluids and the gap between the rotary plate and the casing based on the requirements of the dynamics of MR pin joints. FEM analysis was deployed to study the distribution of the magnetic field along the gap. It is found, from the theoretical analysis and experimental verification, that the MR pin joint with a diameter of 180 mm can produce a torque of up to 30 Nm, which meets requirements for semi-active members in a multi-storey prototype building model in the next stage of research and development.

Study on Damage Emergency Repair Performance of a Simple Beam Embedded with Shape Memory Alloys

Shape memory alloys (SMA) have generated a lot of new ideas in engineering. Application is however so far limited in the field of civil engineering. Sensing and actuation properties of SMA can be applied into civil infrastructures to improve structural performance. This paper presents an integrated self-diagnostic and emergency repair intelligent structure system embedded with shape memory alloy bars by utilizing its sensing as well as actuation properties. And this study is mainly focused on damage repair. It is verified that embedding SMA bars can effectively decrease the moment of the reinforced concrete (RC) beam through the mechanical analysis. In addition, the finite element analysis of the reinforced beam embedded with SMA bars is employed to further investigate the modification on the stress intensity around cracks by SMA bars.

Dynamics and Shape Control of Vibrating Composite Plate Containing Piezoelectric Laminas. Design of an Intelligent Structural Antifouling System

As widely used sensors and actuators, piezoelectric materials have received great attention. Development of the smart structures can offer a great deal potential for use in advanced industry. This paper discuss the feasibility and efficiency of shape control of piezolaminated composite in antifouling process. The idea is to design an intelligent structural system that is able to protect itself against the fouling.

The analysis of thermal stresses in thermopiezoelastic semi-infinite body with an edge crack

Thermopiezoelastic materials have recently attracted considerable attention because of their potential use in intelligent or smart structural systems. The governing equations of a thermopiezoelastic medium are more complex due to the intrinsic coupling effects that take place among mechanical, electrical and thermal fields. In this analysis, we deal with the problem of a crack in a semi-infinite, transversely isotropic, thermopiezoelastic material by means of potential functions and Fourier transforms under steady heat-flux loading conditions. The problem is reduced to a singular integral equation that is solved. The thermal stress intensity factor for a crack situated in a cadmium selenide material is calculated.

Issues in Infrastructure Health Monitoring for Management

The most critical issues that have been identified as being needed to implement meaningful and beneficial applications of health monitoring for infrastructure management are discussed. Issues related to infrastructure health monitoring for management can be defined in three overlapping categories. In this context, engineering tools, methods, and knowledge should be developed and utilized to answer societal and educational aspects of the problem while taking advantage of the information tools and methodologies available today. The need for integrated research, education, and practice for infrastructure management is emphasized. The challenges in the integration of intelligent transportation and structural systems concepts within an optimum integrated asset management framework are described and illustrated. Examples from ongoing research on the health monitoring of short-span bridge families and long-span bridges are presented to illustrate the issues.

Neural Networks for Sensor Fault Correction in Structural Control

Two neural network architectures are proposed for use in structural control applications: a Failure Detection Neural Network and a Failure Accommodation Neural Network. The Failure Detection Network monitors structural responses and automatically detects sensor failures that can reduce control performance and effectiveness, while the Failure Accommodation Network accounts for the failed sensors. Together, the networks are a step toward development of an expert diagnostic system for structural applications. Examples of two simple structures are used to illustrate the features of the networks. Sensor failures are simulated during control operation, and the ability of the networks to detect and accommodate the failures is examined. The numerical results reveal that these networks show promise for automated intelligent fault detection, identification, classification, and accommodation, and as such may have potential use in real civil structures. Although the networks have been used to detect and account for sensor faults alone, they may also be trained for other kinds of failures. Thus, they may have potential for incorporation into an intelligent structural monitoring system.

Expert System for Multidiameter Drill Selection: An Embedded Knowledge Base Approach

This paper describes the development of an expert system for selection of multidiameter drills. These drills are used for stepped hole drilling operations. The structure of an expert system for multidiameter drills is outlined. The aim of this development was to establish a framework for an expert system which uses existing tools to combine a rule-based knowledge base, a database and online help including diagnostics working together within the Windows environment. A new intelligent system structure, operating in the Windows environment, has provided more flexibility and user friendliness than other similar systems.