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The purpose of this paper is to improve autonomous flight performance of a fixed-wing unmanned aerial vehicle (UAV) via simultaneous morphing wingtip and control system design conducted with optimization, computational fluid dynamics (CFD) and machine learning approaches.

The main wing of the UAV is redesigned with morphing wingtips capable of dihedral angle alteration by means of folding. Aircraft dynamic model is derived as equations depending only on wingtip dihedral angle via Nonlinear Least Squares regression machine learning algorithm. Data for the regression analyses are obtained by numerical (i.e. CFD) and analytical approaches. Simultaneous perturbation stochastic approximation (SPSA) is incorporated into the design process to determine the optimal wingtip dihedral angle and proportional-integral-derivative (PID) coefficients of the control system that maximizes autonomous flight performance. The performance is defined in terms of trajectory tracking quality parameters of rise time, settling time and overshoot. Obtained optimal design parameters are applied in flight simulations to test both longitudinal and lateral reference trajectory tracking.

Longitudinal and lateral autonomous flight performances of the UAV are improved by redesigning the main wing with morphing wingtips and simultaneous estimation of PID coefficients and wingtip dihedral angle with SPSA optimization.

This paper originally discusses the simultaneous design of innovative morphing wingtip and UAV flight control system for autonomous flight performance improvement. The proposed simultaneous design idea is conducted with the SPSA optimization and a machine learning algorithm as a novel approach.

The purpose of this paper is to develop a building information modelling (BIM)-based multi-objective optimization (MOO) framework for volumetric analysis of buildings during early design stages. The objective is to optimize volumetric spaces (3D) instead of 2D spaces to enhance space utilization, thermal comfort, constructability and rental value of buildings

The integration of two fundamental concepts – BIM and MOO, forms the basis of proposed framework. In the early design phases of a project, BIM is used to generate precise building volume data. The non-sorting genetic algorithm-II, a MOO algorithm, is then used to optimize extracted volume data from 3D BIM models, considering four objectives: space utilization, thermal comfort, rental value and construction cost. The framework is implemented in context of a school of architecture building project.

The findings of case study demonstrate significant improvements resulting from MOO of building volumes. Space utilization increased by 30%, while thermal comfort improved by 20%, and construction costs were reduced by 10%. Furthermore, rental value of the case study building increased by 33%.

The proposed framework offers practical implications by enabling project teams to generate optimal building floor layouts during early design stages, thereby avoiding late costly changes during construction phase of project.

The integration of BIM and MOO in this study provides a unique approach to optimize building volumes considering multiple factors during early design stages of a project

Construction safety is heavily affected by using new technologies in this growing trend of technology adoption. Especially, safety performance is enhanced through the utilization of some effective technologies such as artificial intelligence, virtual reality, BIM and wearable devices. Therefore, the main purpose of this study is to investigate the influence of emerging technologies on construction safety performance and quantify the relationship between those. The proposed components of emerging technologies are BIM, GIS, VR, RFID, AI, ML, eye tracking and serious games and wearable devices, whereas the dimensions of construction safety performance are safety planning, safety training, safety inspection and monitoring, safety audits and reviews and safety leadership.

A structural model was composed consisting of emerging technologies and safety performance indicators. Then, a questionnaire was designed and administered to construction professionals, and data from 167 projects were analyzed using structural equation modeling. The data were analyzed by using software, called SPSS AMOS.

The analysis of the structural model proves that there is a positive and significant relationship between emerging technologies and construction safety performance. Moreover, the factor loadings for each factor were found to be high indicating a good representation of the construct by the components developed. Among the technologies, BIM, robotics and automation, AI and wearable devices were detected to be the most significant technologies in terms of impacting safety performance.

The study contributes to the body of knowledge in that it develops a conceptual framework consisting of specific technologies in terms of emerging technologies, reveals the impact of such technologies on safety performance and proposes several tools and strategies for enabling effective safety management along the project lifecycle. Industry practitioners may benefit from the framework developed by adopting such technologies to enhance their safety performance on construction projects.

Induction heating applications aided by power electronic control have become very attractive in the recent past. For cooking applications, power electronics circuits are very suitable to feed power to multi loads with an appropriate control technique. The purpose of this paper is to develop a three leg inverter to feed power to three loads simultaneously and independently.

Pulse density modulation control technique is used to control the output power independently with constant switching frequency.

Multi-load handling converter with independent power control is achieved with reduced number of switching devices (two switches/per load) with simple control strategy.

The proposed system is simulated in MATLAB/Simulink, and the thermal analysis is carried out in COMSOL multi-physics software. The hardware realisation is performed for a 1 kW prototype with 20 kHz switching frequency and 10 kHz pulse density modulation frequency. PIC16F877A microcontroller is used to validate the experimental results for various values of control signals (D_PDM). The simulation and experimental results are in good agreement and validates the developed system.

Throughout an aircraft development process, the conceptual design phase is an extremely important milestone; hence, the quality and success of this step directly affect the overall cost and lead time of the project. Because of this fact, the purpose of this study is to provide outputs and suggestions to the designing engineer regarding the requirements for reducing overall design time as well as costs and creating an ideal design at the early phases of the project by optimizing the aircraft development process.

The system has been prepared parametrically and presents some performance specifications for the aircraft in the early phases of the design, for example, coefficients for lift C_L as well as drag C_D and weight as well as fuel estimations. The software uses a combination of well-known design techniques within just one platform in contrast to many other applications. Because of this feature, it is not needed to use different sub-platforms which would require an appropriate environment and even though would lead to complications with regard to the connectivity. The system also presents relevant information about the aircraft performance like velocity versus load factor (V-n) diagrams, maximum turn rate of climb, turn rate and climb angle graphs in contrast to many other open-source conceptual design platforms.

In this study, authentic General Dynamics F-16 Fighting Falcon and McDonnell Douglas F-15 Eagle data were used as input to the system, and advanced geometric and/or performance graphs were obtained and compared to the literature where a good agreement of the results was observed. These results with regard to the aircraft performance are typically product specific and quite rare in the literature. These data obtained by use of the software during the aircraft design are, thus, of major interest, especially for the design of new aerospace platforms. In this study, all of these graphs (especially the remarkable V-n diagram) are obtained on one platform.

The aircraft conceptual design and analysis system software provides information and suggestions regarding the requirements for reducing the overall design time, reducing the design costs and creating an optimized design at the early phases of a project by optimizing the aircraft development process within just one convenient, that is, user friendly, platform, where it uses a combination of varying methodologies. Besides presenting one interface, which is quite typical for conceptual design tools, it allows applications of methods like vortex lattices and finite differences for obtaining aerodynamic performance parameters.