Track Profile Research Articles

Deep insight on efficiency of deposited energy within sensitive volumes for characterizing basic mechanism of single event upset saturated cross-section regarding implicit inaccuracy

The Single Event Upset (SEU) characterization on the partially depleted (PD) Silicon-On-Insulator (SOI) SRAMs manufactured by 0.5/0.35 μm CMOS technology has been studied by using the experimental accelerator’s testing and Monte Carlo simulation. The results show that, in spite of the good consistent between the simulated data and experimental testing, one notable phenomenon is that, linear energy transfer (LET) as the input has no manifest influence on the saturation of SEU cross-section. This non-negligible trend led us to use the term ion velocity instead of LET. The characteristics of ion velocity have certainly been proved by the experiment, while the unsimilar results are found for the simulation with no any difference from the SEU cross-section. Consequently, a more straightforward calculation in the deposited energy within sensitive volume (SV) has performed by inspecting directly into the underlying mechanism of the undetected energy loss. The loss of deposited energy has been obtained in the assumption that the heavy ions strike on the hypothetical device at oblique incidence. The unexpected energy loss resulted from incident ions at oblique incidence as edge effect indicates the importance of quantifying the efficiency of energy collection with respect to the dimensions of SV, including the variance of surface area and thickness. It is illustrated that the deposited energy induced by heavy ions on the condition of changeable surface area has more sensitivity on the incident angle and ionic characterization compared with those for the SV of variable thicknesses. Moreover, it is obtained that the fractional changes of deposited energy within the SVs of different thicknesses present a saturating trend, which can be accelerated by the increment of incident angle, and this evidence would be helpful for deeply comprehending why the implicit inaccuracy of the SEU saturated cross-section happened under the metrics of LET or ion velocity. Ultimately, the dependence of deposited energy on the surface area and thickness is further explored and discussed based on the geometrical property and radial track profile.

Vision-Based Target Tracking Controller Design for Asteroid Flyby Problem

An accurate target tracking system improves the quality of flyby imaging of the target and consequently aids effective planetary exploration. A vision-based tracking system is one of the more popular systems, utilizing imaging data to achieve the required tracking accuracy. However, recent high-accuracy target tracking requirements cannot be achieved with targeting error feedback only. This paper summarizes the asteroid flyby mission characteristics and requirements, shows how possible error sources in the tracking system, and displays an exemplar control system design. The tracking error source is generally divided into a navigation error, which is a tracking profile generation error, and a control error, which is caused by the control system. A high-quality onboard relative-trajectory determination system is required to improve the navigation accuracy of the control system, because the pre-designed or offline-estimated relative trajectory contains uncertainties that cause the tracking profile generation error. Previous studies focused on this navigation error because of its sensitive effect on control system performance, showing some methods for improvement. This paper discusses how the control system can be improved to achieve greater precision during target tracking by considering the navigation and system characteristics. A realistic case study scenario is defined and analyzed based on an actual target tracking interplanetary probe mission. The characteristics of the designed control system are presented and its performance is analyzed via numerical simulation, using the case study data.

A Machine-Learning-Based Approach for Railway Track Monitoring Using Acceleration Measured on an In-Service Train.

In this paper, a novel railway track monitoring approach is proposed that employs acceleration responses measured on an in-service train to detect the loss of stiffness in the track sub-layers. An Artificial Neural Network (ANN) algorithm is developed that works with the energies of the train acceleration responses. A numerical model of a half-car train coupled with a track profile is employed to simulate the train vertical acceleration. The energy of acceleration signals measured from 100 traversing trains is used to train the ANN for healthy track conditions. The energy is calculated every 15 m along the track, each of which is called a slice. In the monitoring phase, the trained ANN is used to predict the energies of a set of train crossings. The predicted energies are compared with the simulated ones and represented as the prediction error. The damage is modeled by reducing the soil stiffness at the sub-ballast layer that represents hanging sleepers. A damage indicator (DI) based on the prediction error is proposed to visualize the differences in the predicted energies for different damage cases. In addition, a sensitivity analysis is performed where the impact of signal noise, slice sizes, and the presence of multiple damaged locations on the performance of the DI is assessed.

Experimental and simulated etched track profiles for two relativistic ions treated under different etching conditions: How to shape different track envelopes

PADC polymer sheets of thickness 650 μm were exposed to normal incident high energy ions of 7 GeV Si and 17.48 GeV Ni with particle density ≈ 103 particles/cm2. Chemical etching was carried out under soft and strong etching conditions, and parameters of track diameter and cone length variation with depths were measured and recorded at successive times during the etching process, including snapshots of the etched track profiles. A computer program using a sophisticated chemical etching model including a variation of the bulk etching rate of the detector material was used. This program uses experimental data of a variable bulk etch rate with depth (Vb (z)) and an average longitudinal (Vt) etching rate, for each etching condition and ion. A good agreement is obtained between simulation and experiment in all cases, which validates the choice of the model used and the constant Vt approximation. It is shown that the same latent track due to a given ion gives different three-dimensional shapes depending on the chemical etching conditions used. The production of etched tracks with funnel shapes is one of the originalities of this work. The simulation tool developed allows for exploring the production of microcavities with specific shapes using polymer sheets exposed to high-energy ions.

Adaptive dynamic programming based composite control for profile tracking with multiple constraints

A composite control method based on adaptive dynamic programming (ADP) is developed to solve the profile tracking problem of the hypersonic gliding vehicle (HGV) with multiple constraints (flight and input constraints). First, based on the framework of the standard profile guidance method, a standard drag acceleration–velocity profile is planned as the tracking target, which satisfies the flight constraints. Second, a composite controller based on ADP and dynamic surface control (DSC) is proposed to track the planned profile and satisfy both the terminal conditions and the input constraint. An ADP method is developed to realize the optimal control through a critic neural network (NN) approximation for the solution of Hamilton–Jacobi–Bellman (HJB) equation. By using DSC method, the steady control is realized. Finally, the states of the closed-loop system and the weight estimation error are proved to be uniformly ultimately bounded, and the effectiveness of the proposed composite control method is verified via simulations.

STUDY COMPANION

The Study Companion Android Application is a comprehensive mobile platform designed to enhance the study experience for students and individuals preparing for academic and competitive exams. The application provides a user-friendly interface that allows users to easily download and upload notes related to their academic subjects and competitive exams. By centralizing study materials in one convenient location, the application simplifies the process of accessing and organizing study materials. The application offers various modules tailored to the specific needs of users. The Home Page module presents two options: "Academic" and "Competitive," allowing users to navigate between their academic subjects and competitive exam materials effortlessly. The My Info module provides a personalized space for users to manage their profile information and track their progress. To ensure a secure and efficient user experience, the application incorporates a Log-in and Register page module, where users can create accounts and securely access their personal information and uploaded notes. Additionally, an Admin module is connected to Firebase, enabling administrators to manage user accounts and handle backend operations effectively. The About module serves as a comprehensive resource, offering an app description and contact information for user support. Users can gain a clear understanding of the application's purpose and easily reach out for assistance or feedback. The Study Companion Android Application employs a robust system architecture, utilizing Firebase for seamless data storage, retrieval, and synchronization. The application has undergone rigorous testing, including unit testing, integration testing, and acceptance testing, to ensure functionality, performance, security, and usability. With its user-centric design, reliable architecture, and efficient functionalities, the Study Companion Android Application aims to provide a seamless and enriching study experience for users. By offering a centralized platform for downloading and uploading study materials, the application empowers users in their academic and competitive exam preparations, promoting knowledge sharing, collaboration, and effective learning.

Studies on crystallization process for pharmaceutical compounds using ANN modeling and model based control

Solvent selection and Controlling of operating parameters play a crucial role in batch cooling crystallization process. Choosing a best solvent for crystallization process involves more experimentation and time. To overcome this problem, an Artificial Neural Network (ANN) model technique is used to predict the carbamazepine form Ⅲ solubility by considering the thermodynamic properties of different solvents i.e. critical temperature, critical pressure, temperature, molecular weight, and acentric factor. The ANN model was trained and evaluated for solubility at various input data sets using experimental solubility data available in the literature. The ANN model with 20 hidden neurons has given the R2 value of 0.9943 which shows that the developed ANN model can be used for the selection of best solvent for batch crystallization process. Further, to determine the optimal cooling profile of batch cooling crystallization process, a multi-objective optimization problem is formulated by considering objectives as minimizing the coefficient of variation (CV) and maximizing the Number mean size (NMS) of crystals subjected to population balance equations using “method of moments” technique. Two types of temperature strategies i.e., piece-wise constant and piece-wise linear are developed and solved using NSGA-Ⅱ dynamic optimization procedure. The optimal NMS value attained through piece-wise linear strategy was 197.1 µm. This value has been increased by 28.3 µm from the nominal case (without optimization) and the coefficient of variation has decreased from 0.951 to 0.76. Further, optimal NMS value attained through piece-wise constant strategy was 205 µm. The value has been increased by 36.2 µm and the coefficient of variation has decreased from 0.951 to 0.73. This proves that the crystal attributes can be improved by optimal cooling temperature profile obtained by multi-objective optimization framework. For implementing the optimal cooling profile an advanced model-based control, i.e., Generic Model Control (GMC) was developed. It was observed that the GMC controller has the good tracking profile with no offset with/without disturbances and small value of root mean square error (RMSE) of 0.0016 using piece-wise constant as set point temperature. Using piece-wise linear as set point temperature, the RMSE value was 0.0018. In particular, it is advantageous to operate the batch cooling crystallization process with piece-wise linear strategy for set point trajectory tracking problems.

Inquiry-based mathematics education and attitudes towards mathematics: tracking profiles for teaching

Research on the relationships between the main constructs underlying inquiry-based learning is rarely reported in mathematics education research. Considering this as a complex problem which is worth to be investigated, the present study aims to provide some empirical evidences that might serve as an insight to support further investigations on the relationships between attitudes towards mathematics and inquiry-based learning approaches. Thus, this study adopts a descriptive research design where no variables are manipulated but observed and measured in order to identify changes depicted in data collection. An instructional design focusing on the nature of mathematical inquiry is carried out with the participation of 304 secondary and high school students, and a clustering approach is used to look at how participants are grouped around certain attitudinal profiles before and after such mathematical practice. The results show how the heterogeneity of attitudinal profiles present in the classroom evolves positively in terms of perceived usefulness of mathematics and mathematical self-concept as perception of competence in mathematics. This fact provides some basis that might be used for further research on the idea that certain forms of development in inquiry-based mathematics education (IBME) based on greater immersion in the nature and culture of mathematics can help students to improve their attitudes towards mathematics.

Influence of Inorganic Additives on the Surface Characteristics, Hardness, Friction and Wear Behavior of Polyethylene Matrix Composites.

The aim of this research was to analyze the effect of inorganic additives on the tribological properties of the high-density polyethylene (HDPE) matrix composite surface. Titanium (Ti) and hexagonal boron nitride (hBN) were added in different mass fractions. The samples were produced by pressing a pre-prepared mixture of granules. The composite samples with the following mass fractions of additives were fabricated: 5% hBN, 10% hBN, 28% Ti-2% hBN, 23% Ti-7% hBN, and 20% Ti-10% hBN. An even distribution of individual additives' concentrations was confirmed. Observations of morphology, surface topography, hardness, and tribological measurements were conducted using reciprocating motion tests with the "pin-on-flat" and rotational tests with the "pin-on-disc" configuration. Subsequently, microscopic observations and measurements of the wear track profile were carried out. Additionally, geometry parameters of the contacting elastic body were calculated for various counter-samples. It was found that the Shore D hardness of samples containing Ti and hBN increased with the Ti content, while the coefficient of friction (COF) value decreased. The addition of hBN alone did not significantly affect the hardness, regardless of the ratio, while the COF increased with the increasing hBN content. The COF value doubled with the addition of 10% hBN (COF = 0.22), whereas the addition of 90% Ti-10% hBN resulted in a decrease in the COF value, to COF = 0.83. The highest hardness value was obtained for the sample containing 28% Ti-2% hBN (66.5), while the lowest was for the sample containing 10% hBN (63.2). The wear track analysis, including its height and width caused by deformation, was detected using a focal differentiation microscope and scanning electron microscopy. Additionally, EDS maps were generated to determine the wear characteristics of the composite.

Operation Control Method for High-Speed Maglev Based on Fractional-Order Sliding Mode Adaptive and Diagonal Recurrent Neural Network

The speed profile tracking calculation of high-speed maglev trains is mainly affected by running resistance. In order to reduce the adverse effects and improve tracking accuracy, this paper presents a maglev train operation control method based on a fractional-order sliding mode adaptive and diagonal recurrent neural network (FSMA-DRNN). First, the kinematic resistance equation is established due to the three types of resistance that occur during the actual operation of a train: air resistance, guide eddy current resistance, and suspension frame generator coil resistance. Then, the FSMA-DRNN control law and parameter update law are designed, and a FSMA-DRNN operation controller is composed of three parts: speed feed forward, fractional-order sliding mode adaptive equivalent control, and diagonal recurrent neural network resistance compensation. Furthermore, by using the designed operation controller, it is proven effective by the Lyapunov theory for the stability of the closed-loop control system. Apart from the proposed theoretical analysis, the proposed approaches are verified by experiments on the high-speed maglev hardware-in-the-loop simulation platform Rt-Lab, in line with the 29.86 km test line and a five-car train from the Shanghai maglev, showing the effectiveness and superiority for operation optimization.

An approach for the estimation of vertical wheel/rail force using dynamic signals

The identification of Wheel/Rail Force (WRF) based on acceleration is a cheaper and convenient way to ensure safe operation. For this purpose, this paper describes an approach for the estimation of Vertical Wheel/Rail Force (VWRF) using dynamic signals from a track inspection train (TIT). Based on the vehicle dynamics theory, a VWRF estimation model is established, by which VWRF can be estimated with the measured vehicle acceleration. Rolling angle is a non-constant and hard-measured value which will affect estimation results. By deducing its relation with the difference between left and right track profiles, it can be got through the Vertical Axle Box Acceleration (VABA) and the length of the axle box. VWRF cannot be estimated only by filtering the Axle Box Acceleration (ABA). The mass participating in vibration (PVM) also has a great influence on it. With many tests and calculations, the relationship between the PVM and the wheelset mass is concluded, which made the estimation results much more accurate. The proposed method provides the basis for online high-precision estimate WRF and ensures safe operation. By comparing with a commercial WRF Inspection System, the railway application results identified that the proposed method can produce a satisfactory result.

Neural Network Trajectory Tracking Control on Electromagnetic Suspension Systems

A new adaptive-like neural control strategy for motion reference trajectory tracking for a nonlinear electromagnetic suspension dynamic system is introduced. Artificial neural networks, differential flatness and sliding modes are strategically integrated in the presented adaptive neural network control design approach. The robustness and efficiency of the magnetic suspension control system on desired smooth position reference profile tracking can be improved in this fashion. A single levitation control parameter is tuned on-line from a neural adaptive perspective by using information of the reference trajectory tracking error signal only. The sliding mode discontinuous control action is approximated by a neural network-based adaptive continuous control function. Control design is firstly developed from theoretical modelling of the nonlinear physical system. Next, dependency on theoretical modelling of the nonlinear dynamic system is substantially reduced by integrating B-spline neural networks and sliding modes in the electromagnetic levitation control technique. On-line accurate estimation of uncertainty, unmeasured external disturbances and uncertain nonlinearities are conveniently evaded. The effective performance of the robust trajectory tracking levitation control approach is depicted for multiple simulation operating scenarios. The capability of active disturbance suppression is furthermore evidenced. The presented B-spline neural network trajectory tracking control design approach based on sliding modes and differential flatness can be extended to other controllable complex uncertain nonlinear dynamic systems where internal and external disturbances represent a relevant issue. Computer simulations and analytical results demonstrate the effective performance of the new adaptive neural control method.

Modelling of washboard effect on unpaved roads experimental evidence on non-cohesive materials

Washboard or corrugation is a common phenomenon in unpaved roads. The washboard effect can be very uncomfortable for the driver, but it can also be very dangerous due to the loss of contact between the wheels and the road. There are few pieces of research about this topic, but undulations seem to emerge due to the caŕs velocity and mass. This work aims to identify the main physical variables controlling the appearance of the washboard effect. For this purpose, an experimental set-up of a multi-pass system was developed. This apparatus consists of a rotating wheel rolling over a sandy path. This model allows evaluation of the evolution of the undulations resulting from the washboard phenomenon and allows relating it to variables such as the dynamic forces and track profile. Different scenarios were evaluated, including wheel velocity, wheel mass, and soil density.

Outcomes of the Gore® Excluder® Iliac Branch Endoprosthesis Using Self Expanding or Balloon-Expandable Stent Grafts for the Internal Iliac Artery Component

Objective: The GORE® EXCLUDER® Iliac Branch Endoprosthesis (IBE; W.L. Gore & Associates, Flagstaff, Arizona) was developed to be used in combination with a self-expanding stent graft (SESG) for the internal iliac artery (IIA) bridging stent. Balloon-expandable stent grafts (BESGs) are an alternative for the IIA, offering advantages in sizing, device tracking, precision, and lower profile delivery. We compared the performance of SESG and BESG when used as the IIA bridging stent in patients undergoing EVAR with IBE. Methods: This is a retrospective review of consecutive patients who underwent EVAR with IBE implantation at a single center from October 2016 to May 2021. Anatomic and procedural characteristics were recorded via chart review and computed tomography (CT) postprocessing software (Vitrea® v7.14). Devices were assigned to SESG vs. BESG groups based on the type of device landing into the most distal IIA segment. Analysis was performed per device to account for patients undergoing bilateral IBE. The primary endpoint was IIA patency, and secondary endpoint was IBE-related endoleak. Results: During the study period, 48 IBE devices were implanted in 41 patients (mean age 71.1 years). All IBE devices were implanted in conjunction with an infrarenal endograft. There were 24 devices in each of the self-expanding internal iliac component (SE-IIC) and balloon-expandable internal iliac component (BE-IIC) groups. The BE-IIC group had smaller diameter IIA target vessels (11.6±2.0 mm vs. 8.4±1.7 mm, p<0.001). Mean follow-up was 525 days. Loss of IIA patency occurred in 2 SESG devices (8.33%) at 73 and 180 days postprocedure, and in zero BESG devices, however, this difference was not statistically significant (p=0.16). There was 1 IBE-related endoleak requiring reintervention during the study period. A BESG device required reintervention due to Type 3 endoleak at 284 days. Conclusions: There were no significant differences in outcomes between SESG and BESG when used for the IIA bridging stent in EVAR with IBE. The BESGs were associated with using 2 IIA bridging stents and were more often deployed in smaller IIA target arteries. Retrospective study design and small sample size may limit the generalizability of our findings. Clinical Impact This series compares postoperative and midterm outcomes of self expanding stent grafts and balloon expandable stent grafts (BESG) when used as the internal iliac stent graft as part of a Gore® Excluder® Iliac Branch Endoprosthesis (IBE). With similar outcomes between the two stent-grafts, our series suggests that some of the advantages of BESG, device sizing, tracking, deployment, and profile, may be able to be leveraged without impacting the mid-term performance of the IBE.

Setting the Tibial Component Rotation Based on Femoral Landmarks Allows Congruent Knee Kinematics in Robotic-Assisted Medial Unicompartmental Knee Replacement.

The accurate positioning of the prosthetic components is essential for achieving successful results in medial unicompartmental knee arthroplasty (mUKA). The tibial component rotation in image-based robotic-assisted UKA is usually based on tibial bony landmarks matched to the pre-operative CT model. The study aimed to evaluate whether setting the tibial rotation on femoral CT-based landmarks allows congruent knee kinematics. We retrospectively analyzed data from 210 consecutive image-based robotic-assisted mUKA cases. In every case, we set the tibia rotation landmark parallel to the posterior condylar axis and centered it on the trochlea groove defined on the preoperative CT scan. The implant positioning was primarily set parallel to this rotation landmark and then adjusted based on tibial sizes avoiding component over- or under-hang. During surgery, we recorded the knee kinematics under valgus stress to reduce the arthritic deformity. A femoral-tibial contact point was recorded over the entire range of motion and displayed as a tracking profile on the tibia implant. The femoro-tibial tracking angle (FTTA) was then calculated based on a tangent line to the femoro-tibial tracking-points and the difference to the femur-based rotation landmark. In 48% of the cases, we could position the tibia component exactly to the femoral rotation landmark, whereas in 52% of cases, minimal adjustments were made to avoid component's under- or over-hang. The mean tibia component rotation (TRA) with reference to our femur-based landmark was +0.24° (SD ± 2.9°). The femur-based tibia rotation landmark showed a high correspondence to the FTTA with 60% of the cases having less than 1° of deviation. Mean FTTA was +0.7° (SD ± 2.2°). The mean difference between the absolute value of the TRA and the FTTA (|TRA| - |FTTA|) was -0.18° (SD ± 2°). Setting the tibial component rotation based on CT scan femoral landmarks and not on tibial anatomical landmarks is a reliable method to obtain congruent knee kinematics during image-based robotic-assisted medial UKA with less the 2° deviations on average.

Determination of the working energy capacity of the on-board energy storage system of an electric locomotive for quarry railway transport during working with a limitation of consumed power

The use of specialized rail rolling stock which is used for transporting ore from the quarry to the crushing plant at mining enterprises is analyzed here. Electric locomotives with an asynchronous traction electric drive and an on-board energy storage system are considered for use. The calculated dependencies of the electric locomotive trac-tive power were analyzed and it was established that on flat sections of the track profile, the movement is carried out with a power that does not exceed 50% of the nominal one. The movement with the nominal power is carried out on the controlled uphill during the cargo half-passage. To ensure the necessary power for movement in such areas, the use of an on-board energy storage system is proposed, which should feed the traction system while limiting the power consumed from the catenary. This happens when the voltage on the pantograph drops to a minimum level. The aim of this work is to determine the on-board energy storage system parameters during the operation of the electric locomotive with limitation of the power consumed from the traction network. Mathemati-cal models of the energy exchange processes in the electric locomotive traction system have been developed. The criteria for comparing options for calculating the parameters of the on-board energy storage system have been proposed. The criteria take into account the reduction of energy consumption during movement, the efficiency of energy storage, and the complete use of the on-board energy storage system in terms of power and working energy capacity. Based on the calculation results, it was determined that the use of an energy storage device with a power of 3,540 kW and an operating energy capacity of 63.5 kWh provides a 10% reduction in energy consumption, which is being consumed while moving along the sample section of the road. The current that can be consumed by an electric locomotive with such parameters of the on-board energy storage system is limited by 600 A.

Cycles optimization to underwater glider standoff tracking profiles with the objective of conserving energy

Optimizing the energy consumption of electric powered underwater glider is critical. The objective of this work is to design the energy optimal cycles for standoff tracking profiles. First, the energy consumption model is developed. The model calculates the energy costs based on the operating time and the power of glider’s main components. The operating time is obtained according to the controllers and the reference control signals. The references of heading angles are generated from the standoff guidance. The cycles of profiles determine others and significantly affect the total energy consumption. To obtain the cycles that saves energy meanwhile satisfies standoff tracking constraints, we propose the optimization framework. Determining the feasible solution involves the non-convex optimization problem. A proximal policy optimization-based method is proposed. Normalized inference input is applied to avoid repetitive optimizations. Simulation results show that the energy consumption differences between ours and the optimal method are less than 0.8%, but the computational time is only a quarter of the energy optimal method.

Modeling of the Wear Process of a Locomotive Wheelset and Rail During Sliding in a Curve

Purpose. This article is aimed at analyzing the wear process of locomotive wheelset and rail bands in curved sections of the rail track using the formalization of the ridge wear indicator for the wheelset slippage cycle. Methodology. In the process of developing a model for the wear of a locomotive wheelset, the phenomenon of slippage during the realization of traction torque was considered and the sliding speed functions at the point of contact between the wheel and the rail were determined. On the basis of the obtained functions, an analytical expression for determining the wear factor of the rims and ridges is proposed. To simplify practical calculations, the concept of the relative wear rate of the wheel ridge is introduced and an analytical expression for its determination is proposed. Findings. Our studies show that the slippage of locomotive wheelsets during the realization of traction torque is one of the decisive factors that determines the wear of the ridges. A significant reduction in the resulting ridge slip during slippage can be achieved by reducing the response time of anti-skid devices. It should also be noted that the resulting slip decreases to a greater extent than the speed of the snowplow protection increases. Originality. In this study, for the first time, a model of the wear process of wheel set tires and rims during locomotive slippage is proposed in a curve, where the wheel rim wear factor is represented as the total work of friction forces per slippage cycle. Practical value. The proposed analytical model can be used to predict the service life of locomotive wheel sets and to standardize train weights on railroad sections with a complex track plan and profile.

Antenna tracking profile generation using mixed-integer linear programming

The increasing demand for the improved quantitative and qualitative performance of Earth observation images requires an increase in image data sizes and satellite agility, and that requires an increased effectiveness of antenna operations transmitting data to a ground station. Here, a mixed-integer linear programming (MILP)-based algorithm generating a tracking profile for an antenna subjected to operational constraints was utilized to maximize data transmission time. The constraints included angle and angular velocity limits. This algorithm considers a transition between two sets of angles for the elevation-over-azimuth mechanism to avoid rapid movement. Data transmission angle ranges are depicted as polygons representing the mission environment as mathematical equations in the MILP model. To reduce computation time, two assumptions were applied to simplify the algorithm, which extracts sampling points that can represent interior points. The proposed algorithm was verified by general imaging mission scenarios from a high-mobility satellite with special mission scenarios (i.e., worst-case scenarios for antenna maneuvers). The results were then compared with the preliminary tracking profile from the ground station searching method, which is a heuristic method. The MILP-based algorithm created solutions where data could be transmitted for 97.87% of the entire contact duration; total maneuvers of azimuth and elevation angles averaged at below 45.49% and 60.88% than of those constantly directed at the ground station, respectively. Operational constraints were satisfied in all scenarios, confirming that the algorithm is well suited to both general and worst-case scenario missions.

Investigating the Wear Behaviors of Silane Coated Silica Filled Glass/Epoxy Nanocomposites

Wear behaviors of silane coated silica (SiO2) nanoparticle-filled glass fiber reinforced polymer composites were investigated depending on the type of silane coating (KH550: -Aminopropyl-triethoxy-silane and KH570: -Methacryloxypropyl-trimethoxy-silane) and nanoparticle percentages within the polymer matrix. Unlike the cases given in most research studies, the silanized silica nanoparticles were used as received. Therefore, the synergistic effects of silanization and nanoparticle reinforcement were successfully applied since the silanization process was eliminated. The matrix modification with the nanoparticles was carried out using an ultrasound homogenizer, and then the modified matrix was reinforced with glass fibers. Scanned electron microscopy revealed the disperse ability of silanized silica nanoparticles within the glass/epoxy composites. The wear behaviors of the developed composites were investigated via a ball-on-disc tribology device. Wear track profiles were obtained depending on the width and depth of the wear. The length of wear track and wear mechanisms were determined by a stereomicroscope. The findings have shown that both types of silane coating and silica nanofiller percentages significantly affected the wear rate of the composite structures.