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Copyright of Ordnance Industry Automation is the property of Editorial Board for Ordnance Industry Automation and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

Copyright of Journal of Harbin University of Science & Technology is the property of Journal of Harbin University of Science & Technology and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

The purpose of this paper is to improve the performance of an aircraft database for a flight simulator. The database for a conventional simulator consists of textfiles on a disk that is then loaded into the main memory; data is retrieved through search and evaluation processes that do not take into account the characteristics of the aircraft database. To improve database performance, the aircraft database is converted into a C library database that is optimizedfor search and evaluation. It is used by linking it to the simulator without loading the aircraft database into global memory. To facilitate this process, an automatic C source code generator is designed and implemented, which converts the aircraft database into a C library database. Performance is evaluated by using the C library database in the simulator. The results indicate that the performance is significantly improved compared to the conventional approach. [ABSTRACT FROM AUTHOR]

This article proposes yet another approach towards looking into causes for attention distribution of an operator of unmanned aerial vehicle. During examination, the operator is being tested at dedicated flight simulator while data are gathered and visualized through a mobile eye tracker. Two work stages are considered sequentially, i.e. building a geometric 2D transformation of region of interest (homography) within an image, and overlaying a dynamic heatmap as well. In the former stage, spontaneous movements of the operator's head, recorded by the video, are eliminated thus enabling the operator to use the mobile eye tracker instead of a desktop-based one. During the latter stage, the distribution of operator's attention over time is displayed. In order to implement the current research, a source code has been developed in C++ for some features readily available in OpenCV library to be used. In addition, data gathered after carrying out flight session are processed and discussed thoroughly. [ABSTRACT FROM AUTHOR]

This article presents to develop a robust control system of spherical motion platform (SMP) capable of controlling six-degree-of-freedom motion, particularly unlimited rotational motion for better virtual reality. The SMP is the new design of a motion manipulator/simulator driven by the frictional force between a set of spherical wheels and cockpit sphere. However, it has intrinsic difficulties in control due to numerous uncertainties, including slipping motion between spherical wheels and cockpit sphere. Inaccurate motion control may degrade human perception as well as tracking performance. In this article, sliding mode control based on a disturbance observer is developed for the SMP to achieve precise motion tracking performance and provide a more realistic environment regardless of kinematic and dynamic uncertainties. Numerical simulation and experimental results with proportional–integral–differential and the robust controllers are compared for step and sinusoidal inputs to demonstrate the feasibility of motion control and tracking performance in spite of uncertainties. Finally, the SMP is operated using two representative flight maneuvers as a flight simulator. The results show that the SMP with the control system can be utilized to provide motion cue for a human on board for virtual reality. [ABSTRACT FROM AUTHOR]

In this article, the research aimed at determining the impact of the intensification of actions on the pilot's cognitive load in a simulated flight is presented. The tests were divided into two groups: pre-flight verification tests and flight tests of increasing intensity. The work was carried out at flight simulator CKAS MotionSim5. Based on the collected data, it has been proved that along with the intensification of the tasks imposed on the pilot, the level of his cognitive load also increases. Further inference leads to the conclusion that cognitive overload is one of the main reasons for pilots' mistakes. The linear relationship between experience and cognitive load has also been proven in the studied group. [ABSTRACT FROM AUTHOR]

Taking into consideration that nowadays the aerospace industry focuses a lot on safety, more durable and stable systems are developed. While the system itself is safer, there is another element that can have a high impact on the overall safety of a flight, namely the human factor. Pilot physiological parameters were measured during a full flight in a fixed cockpit environment using application-specific equipment. The recorded or calculated parameters are used to compute a performance envelope model with the scope of determining the degradation of the pilot's condition during different flight phases or events. Several standardized tests were realized/performed on subjects who were given flight instructions before the test, without knowing beforehand the scenario and events that will occur/take place. This study helps in identifying the limits of pilots in different flight scenarios and the impact on their presumed performance. [ABSTRACT FROM AUTHOR]

The article describes the export data of a flight research simulator experiment. The data show how different forms of presentation affect the behavior of instructions for test subjects. The representation forms algorithm, image and text are examined with regard to the number of top events, error frequencies, execution times and subjectively perceived workload. For this purpose, a study was carried out with n = 93 test persons in the research flight simulator, in which the test persons had the task of landing a passenger aircraft using the autopilot with different representation forms. 14 Possible work errors with 11 different representation forms. Further, there are questionnaire answers from test persons.

In attempting to build neurorobotic systems based on flying animals, engineers have come to rely on existing firmware and simulation tools designed for miniature aerial vehicles (MAVs). Although they provide a valuable platform for the collection of data for Deep Learning and related AI approaches, such tools are deliberately designed to be general (supporting air, ground, and water vehicles) and feature-rich. The sheer amount of code required to support such broad capabilities can make it a daunting task to adapt these tools to building neurorobotic systems for flight. In this paper we present a complementary pair of simple, object-oriented software tools (multirotor flight-control firmware and simulation platform), each consisting of a core of a few thousand lines of C++ code, that we offer as a candidate solution to this challenge. By providing a minimalist application programming interface (API) for sensors and PID controllers, our software tools make it relatively painless for engineers to prototype neuromorphic approaches to MAV sensing and navigation. We conclude our discussion by presenting a simple PID controller we built using the popular Nengo neural simulator in conjunction with our flight-simulation platform.

Protection of the natural environment is a key activity driving development in the transport discipline today. The use of simulators to train civil aviation pilots provides an excellent opportunity to maintain the balance between efficiency and limit the negative impact of transport on the environment. Therefore, we decided to determine the impact of selected simulations of air operations on energy consumption. The aim of the research was to determine the energy consumption of the flight simulator depending on the type of flight operation and configuration used. We also decided to compare the obtained result with the energy consumption of an aircraft of a similar class, performing a similar aviation operation and other means of transport. In order to obtain the results, a research plan was proposed consisting of 12 scenarios differing in the simulated aircraft model, weather conditions and the use of the simulator motion platform. In each of the scenarios, energy consumption was measured, taking into account the individual components of the simulator. The research showed that the use of a flight simulator has a much smaller negative impact on the natural environment than flying in a traditional plane. Use of a motion platform indicated a change in energy consumption of approximately 40% (in general, flight simulator configuration can change energy consumption by up to 50%). The deterioration of weather conditions during the simulation caused an increase in energy consumption of 14% when motion was disabled and 18% when motion was enabled. Energy consumption in the initial stages of pilot training can be reduced by 97% by using flight simulators compared to aircraft training.

This article deals with issues related to the use of flight simulation devices in pilot training. It also discusses the regulations included in the legislation defining the scope of simulator use in flight training processes for particular aviation ratings. In addition, the methods for using flight simulation devices in pilot training and practical training processes are presented, taking into consideration civil and military aviation applications.

INTRODUCTION: This study sought to determine the incidence, severity, and time-course of simulator sickness (SS) among Asian military pilots following flight simulator training. METHODS: A survey was conducted on Republic of Singapore Air Force pilots undergoing simulator training. Each subject completed a questionnaire immediately after (0H), and at the 3-h (3H) and 6-h (6H) marks. The questionnaire included the simulator sickness questionnaire (SSQ) and a subjective scale to rate their confidence to fly. RESULTS: In this study, 258 pilots with a median age of 31.50 yr (range, 21–55 yr) and mean age of 32.61 ± 6.56 yr participated. The prevalence of SS was 48.1% at 0H, 30.8% at 3H, and 16.4% at 6H. Based on a threshold of an SSQ score .10, the prevalence of operationally significant SS was 33.3% at 0H, 13.2% at 3H, and 8.1% at 6H. The most frequent symptoms were fatigue (38.1%), eye strain (29.0%), and “fullness of head” (19.9%). There was no significant difference in mean scores between rotary and fixed wing pilots. Older, more experienced pilots had greater scores at 0H, but this association did not persist. A correlation was found between SSQ score and self-reported confidence. DISCUSSION: To our knowledge, this study is the first to report the prevalence of operationally significant SS in Asian military pilots over serial time points. Most pilots with SS are able to subjectively judge their fitness to fly. Sensitivity analysis suggests the true prevalence of SS symptoms at 3H and 6H to be closer to 23.8% and 12.0%, respectively. [ABSTRACT FROM AUTHOR]

In the article, based on the research, the Tiredness Indicator was proposed. The research concerned the pilot's concentration and reaction time to individual stimuli. They were carried out using a flight simulator - CKAS MotionSim 5, located at the Poznan University of Technology. Measurements were made before and during the flight Analysis of the results showed a periodic course of tiredness characteristics, a marked increase in tiredness in the middle of tests and tiredness of only one sense organ confirmed by the results of reaction time and subjective assessment. Based on the conducted research, it can be stated that tiredness reduces the cognitive abilities of the human brain and extends the reaction time to stimuli. [ABSTRACT FROM AUTHOR]

Past studies have found poorer performance on vertical heading judgement accuracy compared to horizontal heading judgement accuracy. In everyday life, precise vertical heading judgements are used less often than horizontal heading judgements as we cannot usually control our vertical direction. However, pilots judging a landing approach need to consistently discriminate vertical heading angles to land safely. This study addresses the impact of training on participants' ability to judge their touchdown point relative to a target in a virtual environment with a clearly defined ground plane and horizon. Thirty-one participants completed a touchdown point estimation task twice, using three angles of descent (3°, 6° and 9°). In between the two testing tasks, half of the participants completed a flight simulator landing training task which provided feedback on their vertical heading performance; while, the other half completed a two-dimensional puzzle game as a control. Overall, participants were more precise in their responses in the second testing compared to the first (from a SD of ± 0.91° to ± 0.67°), but only the experimental group showed improvement in accuracy (from a mean error of − 2.1° to − 0.6°). Our results suggest that with training, vertical heading judgments can be as accurate as horizontal heading judgments. This study is the first to show the effectiveness of training in vertical heading judgement in naïve individuals. The results are applicable in the field of aviation, informing possible strategies for pilot training. [ABSTRACT FROM AUTHOR]

Induced Travel Demand is a phenomenon (ITD) wherein building new road infrastructure increases private car use. ITD has been measured and corroborated through econometric models that give an account of how much travel demand can be induced after road construction. The latter without claims of causality in their inner structure (black-box approach). Beyond the contributions of black-box models, it is still needed to explain structurally ITD for understanding and identifying its causes. Thus, this approach allows policy-makers to design comprehensive policies to deal with ITD in urban context wherein new roads are still needed to guarantee connectivity. In this paper, we present a white-box flight simulator based on a System Dynamics model to support urban transportation decision-making and address ITD. Through the simulator developed, it is possible to improve the causal understanding of ITD. Besides, although the considered policies to intervene in this phenomenon have a conceptual connotation, the simulator is a means to acquire knowledge of structural complexity underlying the interaction between the policies and ITD. [ABSTRACT FROM AUTHOR]

In attempting to build neurorobotic systems based on flying animals, engineers have come to rely on existing firmware and simulation tools designed for miniature aerial vehicles (MAVs). Although they provide a valuable platform for the collection of data for Deep Learning and related AI approaches, such tools are deliberately designed to be general (supporting air, ground, and water vehicles) and feature-rich. The sheer amount of code required to support such broad capabilities can make it a daunting task to adapt these tools to building neurorobotic systems for flight. In this paper we present a complementary pair of simple, object-oriented software tools (multirotor flight-control firmware and simulation platform), each consisting of a core of a few thousand lines of C++ code, that we offer as a candidate solution to this challenge. By providing a minimalist application programming interface (API) for sensors and PID controllers, our software tools make it relatively painless for engineers to prototype neuromorphic approaches to MAV sensing and navigation. We conclude our discussion by presenting a simple PID controller we built using the popular Nengo neural simulator in conjunction with our flight-simulation platform. [ABSTRACT FROM AUTHOR]

Maintaining and balancing an optimal level of workload is essential for completing the task productively. Fighter aircraft is one such example, where the pilot is loaded heavily both physically (due to G manoeuvering) and cognitively (handling multiple sensors, perceiving, processing and multi-tasking including communications and handling weapons) to fulfill the combat mission requirements. This cognitive demand needs to be analysed to understand the workload of fighter pilot. Objective of this study is to analyse dynamic workload of fighter pilots in a realistic high-fidelity flight simulator environment during different flying workload conditions. The various workload conditions are (a) normal visibility, (b) low visibility, (c) normal visibility with secondary task, and (d) low visibility with secondary task. Though, pilot's flying performance score was good, the physiological measure like heart rate variability (HRV) features and subjective assessment (NASA-TLX) components are found to be statistically significant (p<0.05) between tasks. HRV features such as SD2, SDNN, VLF and total power are found to be significant at all task load conditions. The features LFnu and HFnu are able to differentiate the effect of low visibility and secondary cognitive task, which was imposed as increased task in this study. This result benefits to understand the pilot's task and performance at each flying phase and their cognitive demands during dynamic workload using HRV, which could assist pilot's training schedule in optimal way on simulators as well as in actual flight conditions. [ABSTRACT FROM AUTHOR]

As one of the subsystems of advanced flight simulators, Control Loading System (CLS) enhances the realism of simulation by artificially producing the control forces that occur during the actual flight. In this study, an engineering flight simulator is realized for the purpose of CLS development. The simulator integrates the CLS with a flight dynamics model and a visual system to enable validation with piloted simulations. A linkage type CLS is designed with high torque electric motors, while paying special attention to reconfigurability. Data measured from the actual flight controls is transformed to be input to the CLS by using the proposed systematic procedure. Performance of the designed CLS is investigated, according to the requirements of the international certification standards, by comparing the measured flight control behavior of the simulator with that of the actual aircraft. [ABSTRACT FROM AUTHOR]

The instrument landing system (ILS) is the most popular landing aid in the world. It is a distance-angled support system for landing in reduced visibility, while its task is the safe conduct of the aircraft from the prescribed course landing on the approach path. The aim of this study is to analyse the correctness of the ILS in simulated conditions. The study was conducted using a CKAS MotionSim5 flight simulator in the Simulation Research Laboratory of the Institute of Combustion Engines and Transport at Poznan University of Technology. With the advancement of technical equipment, it was possible to check the operation of the system in various weather conditions. Studies have shown that the impact of fog, rain and snow on the correct operation of the system is marginal. Significant influence has been observed, however, during landing in strong winds.

In the design of the six degrees of freedom (6-DOF) flight simulation system, the unmodeled dynamic, transient performance and steady-state performance of the system are generally concerned. Considering that the model of flight simulation system is highly nonlinear and requires high response speed and high stability, this paper applies L1 adaptive controller to the control of flight simulation platform. The controller has a low-pass filter in feedback loop to avoid high frequencies in the control signals, and the required transient performance can be enhanced by increasing the adaptive gain, which can improve the transient, stability, and smoothness of the flight simulator platform. The performance of the L1 adaptive controller is obtained by comparison with the traditional model reference adaptive controller (MRAC). In addition to maintaining the good transient response of MRAC, the L1 adaptive controller improves the stability of the system. The output amplitude of the actuator is reduced by 39.95%, which effectively reduces the performance requirements of the actuator. Some additional experimental evaluations are carried out to show the performance of the controller.

High-resolution remote sensing images are the key data source for the visual system of a flight simulator for training a qualified pilot. However, due to hardware limitations, it is an expensive task to collect spectral and spatial images at very high resolutions. In this work, we try to tackle this issue with another perspective based on image super-resolution (SR) technology. First, we present a new ultra-high-resolution remote sensing image dataset named Airport80, which is captured from the airspace near various airports. Second, a deep learning baseline is proposed by applying the generative and adversarial mechanism, which is able to reconstruct a high-resolution image during a single image super-resolution. Experimental results for our benchmark demonstrate the effectiveness of the proposed network and show it has reached satisfactory performances.