Search results

Digital media is reshaping architectural design by introducing new tools, methods and workflows. Among various AEC tools, Building Information Modeling (BIM) has gained popularity due to its collaboration platform enabling cross-disciplinary teamwork during whole life cycle of buildings. BIM has further transformed culture and processes associated with design, construction and operation of buildings, hence triggering new building regulations in developed countries. However, in developing countries, BIM implementation is facing several barriers, such as lack of investment in technology and training, hesitation in quitting traditional tools and practices, etc. The purpose of this paper is to highlight potentials of BIM for developing countries, which are in need of more sustainable policies for enhancing their economic and environmental performances.

Throughout the text, a literature review on BIM including its dimensions and benefits, impacts on architectural design and adoption in global and local contexts is provided. In case study, surveys and structured interviews are conducted with BIM user and non-BIM user architects throughout Pakistan. Beyond 2D/3D modeling, the use of BIM applications for sustainable design process such as scheduling (4D), cost estimation (5D), performance analysis and facilities management (6D) is investigated.

Using analytical tools of an online surveying tool and SPSS statistical software, barriers and motivations for BIM implementation in Pakistan are determined. Strategies for further BIM adoption and implementation via “education and training institutions” and “supporting organizations and institutions” are defined.

As a developing country, Pakistan shall be moving the barriers for the spread of BIM technology. Recent research covered the entire AEC sector (Masood et al., 2014; Sohu et al., 2017; Ali et al., 2018), yet this paper focuses specifically on architectural design and practice field. In order to find out experiences and expectations about BIM technology in the architecture sector, professionals are surveyed and four chief architects are interviewed. How far have Pakistani architects adopted BIM? For which project types and scales is BIM more serviceable for them? Which BIM applications are they implementing to overcome the limitations in their professional practice? In Pakistan, where sustainability, in terms of scheduling, cost estimation, performance analysis and facilities management, is an indispensible measure for local practices, has implementation of BIM technology achieved sustainability in architectural design process? What are the motivations of Pakistani architects for becoming BIM users in future?

This paper aims to design an adaptive nonlinear strategy capable of timely detection and reconstruction of faults in the attitude’s sensors of an autonomous aerial vehicle with greater accuracy concerning other conventional approaches in the literature.

The proposed scheme integrates a baseline nonlinear controller with an improved radial basis function neural network (IRBFNN) to detect different kinds of anomalies and failures that may occur in the attitude’s sensors of an autonomous aerial vehicle. An integral sliding mode concept is used as auto-tune weight update law in the IRBFNN instead of conventional weight update laws to optimize its learning capability without computational complexities. The simulations results and stability analysis validate the promising contributions of the suggested methodology over the other conventional approaches.

The performance of the proposed control algorithm is compared with the conventional radial basis function neural network (RBFNN), multi-layer perceptron neural network (MLPNN) and high gain observer (HGO) for a quadrotor vehicle suffering from various kinds of faults, e.g. abrupt, incipient and intermittent. From the simulation results obtained, it is found that the proposed algorithm’s performance in faults detection and estimation is relatively better than the rest of the methodologies.

For the improvement in the stability and safety of an autonomous aerial vehicle during flight operations, quick identification and reconstruction of attitude’s sensor faults and failures always play a crucial role. Efficient fault detection and estimation scheme are considered indispensable for an error-free and safe flight mission of an autonomous aerial vehicle.

The proposed scheme introduces RBFNN techniques to detect and estimate the quadrotor attitude’s sensor faults and failures efficiently. An integral sliding mode effect is used as the network’s backpropagation law to automatically modify its learning parameters accordingly, thereby speeding up the learning capabilities as compared to the conventional neural network backpropagation laws. Compared with the other investigated techniques, the proposed strategy achieve remarkable results in the detection and estimation of various faults.