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The purpose of this paper is to present a comparative study of flight circumstances, dynamic stability characteristics and controllability for two transport aircraft in severe atmospheric turbulence at transonic cruise flight for the purpose to obtain the prevention concepts of injuries to passengers and crew members for pilot training in International Air Transport Association (IATA) – Loss of Control In-flight (LOC-I) program.

A twin-jet and a four-jet transport aircraft encountering severe atmospheric turbulence are the study cases for this paper. The nonlinear unsteady aerodynamic models are established through flight data mining and the fuzzy-logic modeling technique based on the flight data of flight data recorder. This method can be adopted to examine the influence of horizontal wind shear and crosswind on loss of control, dynamic stability characteristics and controllability for transport aircraft in different weights and different sizes in tracking aviation safety of existing different types of aircraft.

The horizontal wind shear or crosswind before the turbulence encounter will easily induce rolling motion and then initiate the sudden plunging motion during the turbulence encounter. The roll rate will increase the oscillatory rolling motion during plunging motion, if the rolling damping is insufficient. The drop-off altitude will be enlarged by the oscillatory rolling motion during the sudden plunging motion.

A lack of the measurement data of vertical wind speed sensor on board to verify the estimated values of damping term is one of the research limitations for this study. The fact or condition of being severe in sudden plunging motion can be judged through the analysis of oscillatory derivatives with both dynamic stability and damping terms.

The roll rate will increase the oscillatory rolling motion during plunging motion, if the rolling damping is insufficient. The drop-off altitude will be enlarged by the oscillatory rolling motion during the sudden plunging motion. The horizontal wind shear or crosswind before the turbulence encounter will easily induce rolling motion and then initiated the sudden plunging motion during the turbulence encounter. If the drift angle is large, to turn off the autopilot of yaw control first and stabilize the rudder by the pedal. When passing through the atmosphere turbulence area, the pilots do not need to amend the heading angle urgently.

The flight safety prevention in avoidance of injuries for passengers and cabin crews is essential for the airlines. The horizontal wind shear or crosswind before the turbulence encounter will easily induce rolling motion and then initiated the sudden plunging motion during the turbulence encounter.

The flight safety prevention in avoidance of injuries for passengers and cabin crews is essential. The present assessment method is an innovation to examine the loss of control problems of aviation safety and promote the understanding of aerodynamic responses of the jet transport aircraft. It is expected to provide a valuable lecture for the international training courses for IATA – LOC-I program after this paper is being published.

The purpose of this paper is to assess the risk of controlled flight into terrain (CFIT) for airlines and to develop a practical method for evaluating and predicting CFIT risk to ensure safe and efficient airline operations.

In accordance with the monitoring project specification issued by the Flight Standards Department of the Civil Aviation Administration of China (CAAC), a preliminary draft of evaluation indicators for CFIT risk was developed based on the literature review and semi-structured interviews. Fifteen aviation experts were then selected and invited to participate in a Delphi method to revise the draft. Analytic hierarchy process (AHP) and entropy weight method were used to determine the combined weight of the indicators. The variable fuzzy set model and quick access recorder (QAR) data were applied to evaluate the CFIT risk of an airline from 2007 to 2018, and the classification results were compared with actual operational data.

The research findings reveal that the six most significant monitoring items affecting CFIT risk are incorrect configuration settings during landing, loss of altitude during climbing, ground proximity warning, G/S deviation, flap extension delay during landing and incorrect takeoff configuration. The CFIT risk of airlines has shown an increasing trend since 2015. The values in 2010, 2017 and 2018 were greater than 2 and less than 2.5, indicating that the CFIT risk is at Level 2, close to Level 3, and the risk is low but approaching medium.

Using the combination weight determined by AHP and entropy weight method to rank the weight of 15 monitoring items, airlines can take necessary measures (simulator training, knowledge training) to reduce the occurrence of monitoring items with high weight to reduce CFIT risk. This risk assessment method can quantitatively evaluate the CFIT risk of airlines and provide theoretical guidance and technical support for airlines to formulate safety management measures and flight training programs, enabling the interconnection between QAR data and flight quality.

The proposed method in this study differs from traditional approaches by offering a quantitative assessment of CFIT risk for airlines and enabling the interconnection between QAR data and flight quality.

This study aims to present a diagnosis method to inspect the structure health for aging transport aircraft based on the postflight data in severe clear-air turbulence at transonic flight. The purpose of this method development is to assist certificate holder of aircraft maintenance factory as a complementary tool for the structural maintenance program to ensure that the transport aircraft fits airworthiness standards.

In this study, the numerical approach to analyze the characteristics of flight dynamic and static aeroelasticity for two four-jet transport aircraft will be presented. One of these two four-jet transport aircraft is an aging one. Another one is used to demonstrate the order of magnitude of the static aeroelastic behaviors. The nonlinear unsteady aerodynamic models are established through flight data mining and the fuzzy-logic modeling technique based on postflight data. The first and second derivatives of flight dynamic and static aeroelastic behaviors, respectively, are then estimated by using these aerodynamic models.

Although the highest dynamic pressure of aging aircraft is lower, the highest absolute value of static aeroelastic effects response to the wing of aging aircraft is about 3.05 times larger than normal one; the magnitude variations of angles of attack are similar for both aircrafts; the highest absolute value of the static aeroelastic effects response to the empennage of aging aircraft is about 29.67 times larger than normal one in severe clear-air turbulence. The stabilizer of aging aircraft has irregular deviations with obvious jackscrew assembly problems, as found in this study.

A lack of the measurement data of vertical wind speed sensor on board to verify the estimated values of damping term is one of the research limitations of this study. This research involved potential problem monitoring of structure health for transport aircraft in different weights, different sizes and different service years. In the future research, one can consider more structural integrity issues for other types of aircraft.

It can be realized from this study that the structure of aging transport aircraft may have potential safety threat. Therefore, when the airline managed aging transport aircraft, it ought to be conducted comprehensive and in-depth inspections to reduce such safety risks and establish a complete set of safety early warning measures to deal with the potential problem of aircraft aging.

It can be realized that the structure of aging transport aircraft has potential safety threat. The airline managed aging transport aircraft; it should conduct comprehensive and in-depth inspections to reduce safety risks and establish a complete set of safety early warning measures.

This method can be used to assist airlines to monitor aging transport aircraft as a complementary tool of structural maintenance program to improve aviation safety, operation and operational efficiency.

Reducing aircraft fuel consumption has become a paramount research area, focusing on optimizing operational parameters like speed and altitude during the cruise phase. However, the existing methods for fuel reduction often rely on complex experimental calculations and data extraction from embedded systems, making practical implementation challenging. To address this, this study aims to devise a simple and accessible approach using available information.

In this paper, a novel analytic method to estimate and optimize fuel consumption for aircraft equipped with jet engines is proposed, with a particular emphasis on speed and altitude parameters. The dynamic variations in weight caused by fuel consumption during flight are also accounted for. The derived fuel consumption equation was rigorously validated by applying it to the Boeing 737–700 and comparing the results against the fuel consumption reference tables provided in the Boeing manual. Remarkably, the equation yielded closely aligned outcomes across various altitudes studied. In the second part of this paper, a pioneering approach is introduced by leveraging the particle swarm optimization algorithm (PSO). This novel application of PSO allows us to explore the equation’s potential in finding the optimal altitude and speed for an actual flight from Algiers to Brussels.

The results demonstrate that using the main findings of this study, including the innovative equation and the application of PSO, significantly simplifies and expedites the process of determining the ideal parameters, showcasing the practical applicability of the approach.

The suggested methodology stands out for its simplicity and practicality, particularly when compared to alternative approaches, owing to the ready availability of data for utilization. Nevertheless, its applicability is limited in scenarios where zero wind effects are a prevailing factor.

The research opens up new possibilities for fuel-efficient aviation, with a particular focus on the development of a unique fuel consumption equation and the pioneering use of the PSO algorithm for optimizing flight parameters. This study’s accessible approach can pave the way for more environmentally conscious and economical flight operations.

The purpose of this study is to develop an operational level decision support system model for air traffic controllers (ATCos) within the framework of the Flexible Use of Airspace (FUA) concept to enable more efficient use of airspace capacity. This study produces a systematic solution to the route selection process so that the ATCo can determine the most efficient route with an operational decision support system model using Dijkstra’s Shortest Path Algorithm.

In this study, a new decision support system model for ATCos in decision-making positions was recommended and used. ATCos use this model as a main model for determining the shortest and safest route for aircraft as an operational-level decision support system. Dijkstra Algorithm, used in the model, is defined step by step and then explained with the pseudocode.

It has been determined that when the FUA concept and DSS are used while the ATCo chooses a route, significant fuel, time and capacity savings are achieved in flight operations. Emissions resulting from the negative environmental effects of air transportation are reduced, and significant capacity increase can be achieved. The operational level decision support system developed in the study was tested with 55 scenarios on the Ankara–Izmir flight route compared to the existing fixed route. The results for the proposed most efficient route were achieved at 11.22% distance (nm), 9.36%-time (min) savings and 837.71 kg CO₂ emission savings.

As far as the literature is reviewed, most studies aimed at increasing airspace efficiency produce solutions that try to improve rather than replace the normal process. Considering the literature positioning of this study compared to other studies, the proposed model provides a new systematic solution to the problems that cause human-induced route inefficiency within the framework of the FUA concept.

The technical report released by the National Transportation Safety Board, along with the primary flight cockpit voice recorder data and archival interview data, were used as the basis for this case. Other available public data such as news reports were used to round out the synopsis of the case study.

United Express Flight 5925 was a scheduled commuter passenger flight operated by Great Lakes Airlines with a Beechcraft 1900 twin turboprop. It was a regularly scheduled flight from Chicago O'Hare International Airport to Quincy, Illinois, with an intermediate stop in Burlington, Iowa. Drawing from various first-hand accounts (cockpit voice recorder) and secondary evidence (news reports, archival interview data, and online sources) of the tragedy, the case provides a detailed account of the key events that took place leading up to the accident at Quincy regional airport. The case describes how the radio interactions, a jammed door and degradation of situational awareness all contributed to the accident. Through many of the quotes in the text and eyewitness accounts, readers gain an understanding of the impressions and perceptions of the pilots, including how they felt about many of the critical decisions in the last minutes of the flight and the situation at the airport.

When the authors teach this case, the students are required to read it as pre-reading before class. Various readings and materials (see supplemental readings below and Exhibit 3) are made available to students before class, and the instructor can choose to use some of these materials to further explore areas of interest. This case is best explored over a 90-min session but could be expanded to take up one 3-h session. This case can be covered in an undergraduate senior capstone organizational behaviour seminar, any general organizational behaviour class (including introductory in nature), an undergraduate communication theory class or an MBA class that focuses on applied organizational behaviour concepts. It works particularly well in the MBA class, as students with work experience can make the links between the behaviours explored in the case and their everyday workplaces.

The crane plays an essential role in modern construction sites as it supports numerous operations and activities on-site. Additionally, the crane produces a big amount of data that, if analyzed, could significantly affect productivity, progress monitoring and decision-making in construction projects. This paper aims to show the usability of crane data in tracking the progress of activities on-site.

This paper presents a pattern-based recognition method to detect concrete pouring activities on any concrete-based construction sites. A case study is presented to assess the methodology with a real-life example.

The analysis of the data helped build a theoretical pattern for concrete pouring activities and detect the different phases and progress of these activities. Accordingly, the data become useable to track progress and identify problems in concrete pouring activities.

The paper presents an example for construction practitioners and researcher about a practical and easy way to analyze the big data that comes from cranes and how it is used in tracking projects' progress. The current study focuses only on concrete pouring activities; future studies can include other types of activities and can utilize the data with other building methods to improve construction productivity.

The proposed approach is supposed to be simultaneously efficient in terms of concrete pouring detection as well as cost-effective. Construction practitioners could track concrete activities using an already-embedded monitoring device.

While several studies in the literature targeted the optimization of crane operations and of mitigating hazards through automation and sensing, the opportunity of using cranes as progress trackers is yet to be fully exploited.

Data traffic through wireless communication is significantly increasing, resulting in the frequency of streaming applications as various formats and the evolution of the Internet of Things (IoT), such as virtual reality, edge device based transportation and surveillance systems. Growth in kind of applications resulted in increasing the scope of wireless communication and allocating a spectrum, as well as methods to decrease the intervention between nearby-located wireless links functioning on the same spectrum bands and hence to proliferation for the spectral efficiency. Recent advancement in drone technology has evolved quickly leading on board sensors with increased energy, storage, communication and processing capabilities. In future, the drone sensor networks will be more common and energy utilization will play a crucial role to maintain a fully functional network for the longest period of time. Envisioning the aerial drone network, this study proposes a robust high level design of algorithms for the drones (group coordination). The proposed design is validated with two algorithms using multiple drones consisting of various on-board sensors. In addition, this paper also discusses the challenges involved in designing solutions. The result obtained through proposed method outperforms the traditional techniques with the transfer rate of more than 3 MB for data transfer in the drone with coordination

Fair Scheduling Algorithm (FSA) using a queue is a distributed slot assignment algorithm. The FSA executes in rounds. The duration of each round is dynamic based upon the delay in the network. FSA prevents the collision by ensuring that none of the neighboring node gets the same slot. Nodes (Arivudainambi et al., 2019) which are separated by two or more hopes can get assigned in the same slot, thereby preventing the collision. To achieve fairness at the scheduling level, the FSA maintains four different states for each node as IDLE, REQUEST, GRANT and RELEASE.

A multi-unmanned aerial vehicle (UAV) system can operate in both centralized and decentralized manner. In a centralized system, the ground control system will take care of drone data collection, decisions on navigation, task updation, etc. In a decentralized system, the UAVs are unambiguously collaborating on various levels as mentioned in the centralized system to achieve the goal which is represented in Figure 2.

However, the multi-UAVs are context aware in situations such as environmental observation, UAV–UAV communication and decision-making. Independent of whether operation is centralized or decentralized, this study relates the goals of the multi-UAVs are sensing, communication and coordination among other UAVs, etc. Figure 3 shows overall system architecture.

The individual events attempts in the UAV’s execution are required to complete the mission in superlative manner which affects in every multi UAV system. This multi UAV systems need to take a steady resolute on what way UAV has to travel and what they need to complete to face the critical situations in changing of environments with the uncertain information. This coordination algorithm has certain dimensions including events that they needs to resolute on, the information that they used to make a resolution, the resolute making algorithm, the degree of decentralization. In multi UAV systems, the coordinated events ranges from lower motion level.

This study has proposed a novel self-organizing coordination algorithm for multi-UAV systems. Further, the experimental results also confirm that is robust to form network at ease. The testbed for this simulation to sensing, communication, evaluation and networking. The algorithm coordination has to testbed with multi UAVs systems. The two scheduling techniques has been used to transfer the packets using done network. The self-organizing algorithm (SOA) with fair scheduling queue outperforms the weighted queue scheduling in the transfer rate with less loss and time lag. The results obtained through from Figure 10 clearly indicates that the fair queue scheduling with SOA have several advantages over weighted fair queue in different parameters.

This study aims to develop an extended social attachment model for expatriates, integrating a multiple stakeholder perspective, to understand evacuation decisions during disasters.

Through interviews with 12 Tokyo-based expatriates who experienced the 2011 Tohoku earthquake, tsunami and nuclear disasters, this study collects the lived experiences of a diverse set of expatriates. This data is analyzed abductively to map relevant evacuation factors and to propose a reaction typology.

While the 2011 Tohoku disasters caused regional destruction and fears of nuclear fallout, Tokyo remained largely unscathed. Still, many expatriates based in Tokyo chose to leave the country. Evacuation decisions were shaped by an interplay of threat assessment, location of attachment figures and cross-cultural adjustment. The study also discusses the influence of expatriate types.

Disaster planning is often overlooked or designed primarily with host country nationals in mind. Expatriates often lack the disaster experience and readiness of host country nationals in disaster-prone regions in Asia and beyond, and thus might need special attention when disaster strikes. This study provides advice for how to do so.

By unpacking the under-researched and complex phenomenon of expatriate reactions to disasters, this study contributes to the fields of international human resource and disaster management. Specifically, seven proposition on casual links leading to expatriate evacuation are suggested, paving the way for future research.

This research is associated with the real-time parameters of wide- and narrow-body aircraft to recognize the quantitative relationship framework. This paper aims to find the superiority of aircraft design technology which triggers the reduction in specific fuel consumption (SFC) and economic competitiveness.

The real case study is performed with 22 middle-of-the-market (MoM) aircraft. This paper develops a fuel burn mathematical model for mid-size transport aircraft by a multi-linear regression approach. In addition, sensitivity analysis is performed to establish the authentication of the fuel burn model.

The study reveals that the MoM aircraft would be the future aircraft design in terms of better fuel economy and carbon footprint. From the multi-regression analysis, it is observed that the logarithmic regression model is the best fit for estimating the SFC. Moreover, fineness ratio, aspect ratio, gross weight, payload weight fraction, empty weight fraction), fuel weight fraction, payload, wing loading, thrust loading, range, take-off distance, cruise speed and rate of climb are observed as the suitable parameters which provide the best fitness value as 0.9804.

Several existing literature reveals that a few research has been performed on the MoM aircraft with wide-body configuration. Moreover, mathematical modelling on the fuel consumption was insignificantly found. This study examines several parameters which affect the fuel consumption of a wide-body aircraft. A real-case study for design configurations, propulsive systems, performance characteristics and structural integrity parameters of 22 different MoM aircraft are performed. Moreover, multi-regression modelling is developed to establish the relation between SFC and other critical parameters.