Discover the Latest Journals in Architecture and Architectonics

Architecture is both the process and product of planning, designing, and constructing a building or structure, while architectonics is the scientific study of architecture itself. Architectural works are often considered important cultural symbols and works of art, and we often identify past civilizations with their architectural heritage.

Architecture and Architectonics

You are looking at 81 - 90 of 1,930 items for

  • Refine by Access: All Content x
Clear All

Abstract

The redundant manipulators have more DOFs (degree of freedoms) than it requires to perform specified task. The inverse kinematic (IK) of such robots are complex and high nonlinear with multiple solutions and singularities. As such, modern Artificial Intelligence (AI) techniques have been used to address these problems. This study proposed two AI techniques based on Neural Network Genetic Algorithm (NNGA) and Particle Swarm Optimization (PSO) algorithm to solve the inverse kinematics (IK) problem of 3DOF redundant robot arm. Firstly, the forward kinematics for 3 DOF redundant manipulator has been established. Secondly, the proposed schemes based on NNGA and PSO algorithm have been presented and discussed for solving the inverse kinematics of the suggested robot. Thirdly, numerical simulations have been implemented to verify the effectiveness of the proposed methods. Three scenarios based on triangle, circular, and sine-wave trajectories have been used to evaluate the performances of the proposed techniques in terms of accuracy measure. A comparison study in performance has been conducted and the simulated results showed that the PSO algorithm gives 7% improvement compared to NNGA technique for triangle trajectory, while 2% improvement has been achieved by the PSO algorithm for circular and sine-wave trajectories.

Open access

Abstract

Various developing countries are confronted with serious environmental difficulties due to excessive resource utilization and insufficient waste management system. In particular, construction and demolition waste poses a grave threat to the environment, contributing to escalating energy consumption, the depletion of landfill capacities, and the generation of harmful noise and dust pollution. Consequently, the research community is tasked with the daunting challenge of devising effective strategies to incorporate this waste material in producing concrete, without compromising the critical strength and durability characteristics. The investigation aims to attain the aforementioned objective by examining the effects of using recycled aggregates as a distinct partial replacement of 0%, 5%, 10%, 15%, and 20% on the compressive and split tensile strength traits, contingent upon 7 and 28 days of age of curing. Experimental test results show that the optimal concrete production is achieved when 10% of coarse aggregate is replaced with recycled aggregate, maintaining 98% of the materials compressive and split tensile strength. To further validate the obtained experimental data, model equations were derived through regression analysis and the framed model equation is further assessed for accuracy using error analysis. In this study, a MATLAB program was utilized for prediction of compressive and split tensile strength with five distinct network types and the Levenberg-Marquardt algorithm is used for optimization. A comparative analysis was conducted between the regression analysis values and the performance of the ANN modelling. The findings demonstrate that the Artificial Neural Network (ANN) serves as a highly effective model, offering significantly improved accuracy in predicting the optimal correlation between compressive strength and split tensile strength of concrete.

Open access

Abstract

This study has developed adaptive synergetic control (ASC) algorithm to control the angular position of moving plate in the electronic throttle valve (ETV) system. This control approach is inspired by synergetic control theory. The adaptive controller has addressed the problem of variation in systems parameters. The control design includes two elements: the control law and adaptive law. The adaptive law is developed based on Lyupunov stability analysis of the controlled system, and it is responsible for estimating the potential uncertainties in the system. The effectiveness of the proposed adaptive synergetic control has been verified by numerical simulation using MATLAB/Simulink. The results showed that the ASC algorithm could give good tracking performance in the presence of uncertainty perturbations. In addition, a comparison study has been made to compare the tracking performance of ASC and that based on conventional synergetic control (CSC) for the ETV system. The simulated results showed that the performance of ASC outperforms that based on CSC. Moreover, the results showed that the estimation errors between the actual and estimated uncertainties are bounded and there is no drift in the developed adaptive law of ASC.

Open access

Abstract

The Cyber-Physical and Vehicle Manufacturing Laboratory, a model Industry 4.0 laboratory, is applying new innovative solutions to improve the quality of education. As part of this, a digital twin of the lab was designed and built, where users can practice. In the virtual space, it is possible to apply the known robot motion types, and the tool centre and wrist speed have been measured virtually. Robot control tasks can be performed “offline” using parameters. This information can then be transferred to the actual physical robot unit. The stable diffusion 1.5 deep learning model generates 2D geometric shapes for trajectory, allowing users to perform unique tasks during education. The Google Colab cloud-based service was used to teach our rendered-type dataset. For the 3D simulation frame, we used V-REP, which was developed on a desktop PC equipped with an Intel Core i5 7600K processor, Nvidia GTX1070 VGA with 8 GB of DDR5 VRAM, and 64 GB of DDR4 memory modules. The following material describes an existing industrial six-axis robot arm and its implementation, which can be controlled and programmed while performing virtual measurements after integrating into a Cyber-Physical system and using deep learning techniques.

Open access
International Review of Applied Sciences and Engineering
Authors:
Wajahat Saeed
,
Muhammad Sohail Saleh
,
Muhammad Naqash Gull
,
Hassan Raza
,
Rafaqat Saeed
, and
Tahira Shehzadi

Abstract

With the escalating density of vehicles converging at road intersections, the surge in road accidents, traffic conflicts, and traffic congestion has emerged as a pressing concern. This research paper addresses these challenges by employing MC (manual control) techniques to mitigate encroachment issues at three selected intersections. These intersections were identified through a comprehensive analysis of the Ranking-based Instance Selection (RIS), enabling the design of suitable measures to facilitate smooth traffic flow and minimize the occurrence of crashes. In order to gather pertinent data, the study incorporates various parameters such as traffic volume, peak flow rate (PFR), traffic conflicts, accidents, and intersection inventory. Through the implementation of our proposed approaches, which involve both MC techniques and signalized operation, a supreme level of service (LOS) is attainable. Notably, our findings demonstrate a remarkable reduction in the volume-to-capacity ratio (v/c ratio) of up to 0.62. This paper thus serves as a significant contribution to the field of traffic management, offering practical insights for optimizing intersection design and effectively addressing the challenges posed by increased traffic density.

Open access

Abstract

Worldwide, precast and hybrid construction methods are becoming increasingly popular in the construction industry. But many problems occur during the fabrication, such as segregation, bleeding, scaling, plastic shrinkage, dust formation, honeycombing, sintering, high sorptivity, and high permeability and transportation. This problem may be caused by an ineffective curing process that affects the quality of concrete and construction. In addition, it provides inadequate and incomplete cement hydration that has a 20% negative effect on the desired properties of the concrete. Various researchers have demonstrated the components of self-curing lightweight concrete that can enhance strength and physicochemical properties, and address the above-mentioned issues. In this review, the role of the self-curing mechanism in lightweight concrete based on the various self-curing chemical admixtures such as polyethylene glycol (PEG), superabsorbent polymer (SAP), polyvinyl alcohol (PVA), sodium lignosulfonate and calcium lignosulfonate as self-curing agents are discussed in detail. Also, this paper briefly reports on the scope, significance, mechanisms, and tests for self-curing lightweight concrete. Overall, this review analyzes the possibilities of future research perspectives on self-curing lightweight concrete with sustainable materials and fibres with comparative technical information.

Open access

Abstract

Sensors are the main components in Cyber-Physical Systems (CPS), which transmit large amounts of physical values and big data to computing platforms for processing. On the other hand, the embedded processors (as edge devices in fog computing) spend most of their time reading the sensor signals as compared with computing time. The impact of sensors on the performance of fog computing is very great, thus, the enhancement of the reading time of sensors will positively affect the performance of fog computing, and solves the CPS challenges such as delay, timed precision, temporal behavior, energy, and cost. In this paper, we propose an algorithm based on the 1st derivative of the sensor signal to generate an adaptive sampling frequency. The proposed algorithm uses an adaptive frequency to capture the sudden and rapid change in sensor signal in the steady state. Finally, we realize and tested it using the Ptolemy II Modeling Environment.

Open access

Abstract

This study examines the economic optimisation of existing district heating systems. A new approach has been taken to solving a long-standing problem. The authors describe the input-output model of the system, the balance equations for the thermal equilibrium of the system, and the heat transfer system. From the balance equations of the series-connected system elements, the resultant heat transfer balance equation and the resultant power transmission equation are derived. In an example, the authors detailed how perturbations in some input variables can be corrected with other variables. The equations presented and the concepts introduced form absolutely new scientific results.

Open access

Abstract

Selecting the construction delivery method during the contracting period is one of the most important decisions determining the quality of large-scale infrastructure projects. Infrastructure projects have the most complex production processes in civil engineering. Infrastructure projects are among the most complex and resource-intensive endeavours in civil engineering due to their size, scope, multidisciplinary nature, regulatory requirements, financing challenges, environmental considerations, and the need for long-term planning and maintenance. Effective project management, collaboration, and a deep understanding of these challenges are crucial for the successful execution of infrastructure projects. Implementing such projects inevitably demands proper quality management throughout the project lifecycle. Two primary types of construction contracts are under implementation worldwide: Design-Bid-Build (DBB) and Design–and–Build (DB) contracts. In the Western Balkans region, both types of contracts are utilized for infrastructure projects, A noticeable trend is emerging toward transitioning from DBB to DB contracts. This paper provides a comprehensive analysis of quality management within the context of construction contracts with a focus on the roles and responsibilities of key stakeholders and how these factors affect the achievement of quality objectives while managing constraints related to cost and time. This research aims to improve construction practices by selecting an adequate type of contract for construction practices and ensuring successful project outcomes.

Open access