Aircraft Platforms Research Articles

Evaluating Reduced-Order Urban Wind Models for Simulating Flight Dynamics of Advanced Aerial Mobility Aircraft

Advanced Aerial Mobility (AAM) platforms are poised to begin high-density operations in urban areas nationwide. This new category of aviation platforms spans a broad range of sizes, from small package delivery drones to passenger-carrying vehicles. Unlike traditional aircraft, AAM vehicles operate within the urban boundary layer, where large structures, such as buildings, interrupt the flow. This study examines the response of a package delivery drone, a general aviation aircraft, and a passenger-carrying urban air mobility aircraft through an urban wind field generated using Large Eddy Simulations (LES). Since it is burdensome to simulate flight dynamics in real-time using the full-order solution, reduced-order wind models are created. Comparing trajectories for each aircraft platform using full-order or reduced-order solutions reveals little difference; reduced-order wind representations appear sufficient to replicate trajectories as long as the spatiotemporal wind field is represented. However, examining control usage statistics and time histories creates a stark difference between the wind fields, especially for the lower wing-loading package delivery drone where control saturation was encountered. The control saturation occurrences were inconsistent across the full-order and reduced-order winds, advising caution when using reduced-order models for lightly wing-loaded aircraft. The results presented demonstrate the effectiveness of using a simulation environment to evaluate reduced-order models by directly comparing their trajectories and control activity metrics with the full-order model. This evaluation provides designers valuable insights for making informed decisions for disturbance rejection systems. Additionally, the results indicate that using Reynolds-averaged Navier–Stokes (RANS) solutions to represent urban wind fields is inappropriate. It was observed that the mean wind field trajectories fall outside the 95% confidence intervals, a finding consistent with the authors’ previous research.

Aircraft Electrothermal Pulse Deicing

Abstract Ice formation and accumulation on aircraft is a major problem in aviation. Icing is directly responsible for aircraft incidents, limiting the safety of air travel and requiring expensive, and sometimes ineffective deicing strategies. Furthermore, electrification of aircraft platforms leads to difficulties with integration of legacy deicing methods such as pneumatic boots. In this work, we study electrothermal pulse deicing capable of efficient and rapid removal of ice from aircraft wings. The pulse approach enables the efficient melting of a thin (<100 μm) ice layer on the wing surface to limit parasitic heat losses. Only the interface is melted, with the rest of the ice sliding on the melt lubrication layer due to aerodynamic forces. To study pulse deicing, we developed a transient thermal-hydrodynamic numerical model that accounts for multiple phases and materials, specific and latent heating effects, melt layer hydrodynamics, as well as boundary layer effects. To identify optimal deicing strategies, we use our model to study the effects of heater thickness (50 μm < th < 1 mm), substrate electrical insulation thickness (10 μm < ti < 1 mm), pulse duration (0.4 s < Δtpulse < 4.5 s), and pulse energy. Optimum operating points are identified for large (Boeing-747), midsize (Embraer-E175), and small (Cessna-172) aircraft. The scale-dependent thermal-hydraulic model results are used to estimate input conditions required for deicing and integrated into an electrical model considering energy storage, power electronics, integration, and layout, to achieve overall volumetric and gravimetric power density optimization.

Burden and Risk Factors of Cervical Spine Conditions in Military Aircrew From 1997 to 2015: A Retrospective Cohort Study.

Military aviators may have increased risk of cervical spine injuries because of exposure to supraphysiologic forces and vibration during dynamic flight. Aviator medical attrition impairs mission readiness, decreases operational capabilities, increases overall DoDcosts, and decreases retention of seasoned aviators. This study evaluated incidence and risk factors for cervical spine conditions in U.S. military aviators from 1997 to 2015. The Defense Medical Epidemiological Database was queried for aviators with a diagnosis of cervical spine conditions. Pertinent ICD-9 codes for cervical spine pathology were ascertained from U.S. Army, Air Force, and Naval Air Forces aeromedical references. Negative binomial regressions assessed sex, age, service, aircraft, and year on incidence of conditions. Rates were compared to non-aviator controls. The study was approved by the Institutional Review Board at the Naval Health Research Center (NHRC.2020.0205-NHSR). Incidence rates were 9.78 to 12.57/1,000 person-years for neck pain, 2.04 to 3.89/1,000 person-years for degenerative conditions without neurological involvement, and 0.94 to 1.36/1,000 person-years for degenerative conditions with neurological involvement. Aviation occupation (relative risk [RR] 1.41-2.05), female sex (RR 3.32-7.89), age over 40 (RR 2.39-4.62), and service in the Army or Marine Corps (RR 1.62-2.14) were risk factors. Military aviators had a statistically significant increase in risk of neck pain and medically disqualifying degenerative cervical spine conditions compared to non-aviator controls. Rates of neck pain increased in all aviators over the study epoch. Possible explanations could be related to the operational demands and the increased use of forward helmet-mounted display systems during the study period, a supposition that requires further investigation. There was no significant difference in rates of neck pain or degenerative cervical conditions between aircraft platforms (fighter/bomber, other fixed wing, and rotary wing). Female sex, age over 40 years, and Army/Marine Corps service were the greatest risk factors for neck pain and degenerative cervical spine conditions. Targeted prevention programs and expanded treatment modalities are necessary to reduce aviator attrition and Department of Defense cost burden.

Direct Combat-related U.S. Army Aviation Injuries 2003-2014.

The U.S. Army Aeromedical Research Laboratory (USAARL), a partner in the Joint Trauma Analysis for the Prevention of Injury in Combat (JTAPIC) partnership, conducted a series of retrospective reviews to investigate injuries sustained by occupants of U.S. Army rotary-wing aircraft involved in combat damage incidents. The reviews were conducted to provide occupant survivability information to the Aviation Survivability Development and Tactics team, an agency within the U.S. Army Aviation Center of Excellence. For these reviews, combat damage incidents that produced casualties were separated into direct events (i.e., events in which an enemy weapon system directly injured occupants) and indirect events (i.e., incidents in which occupants were injured as a result of a crash caused by the enemy weapon system). The previous USAARL reviews provided an overview of injuries sustained during direct and indirect events. The objective of this review was to conduct a detailed analysis of injuries occurring during direct events. A descriptive retrospective review was conducted on injuries sustained by occupants of U.S. Army rotary-wing aircraft involved in combat damage incidents between 2003 and 2014. All Black Hawk, Apache, and Chinook combat aviation damage incidents for the study period were reviewed. Personnel casualty information from the Defense Casualty Information Processing System (DCIPS) was linked to combat damage incident information by matching the aircraft platform, incident date, and circumstantial information found in incident narratives. Injury information for personnel identified in DCIPS as being wounded in action was obtained from the JTAPIC partnership; injury data for personnel killed in action were retrieved from the Armed Forces Medical Examiner System. All injuries were coded using the Abbreviated Injury Scale (AIS). Descriptive statistics were used to describe the frequency and distribution of injuries to personnel involved in direct events. Overall, the extremities were the most commonly injured body regions, with lower extremities suffering more injuries than upper extremities. Penetrating injuries were identified as the primary injury mechanism for all body regions. Injuries to each AIS body region were predominantly of minor (AIS 1) and moderate (AIS 2) severity. Although injury severities were generally low (AIS 1 or AIS 2), the results of this effort indicate which body regions may benefit from additional protection during rotary-wing operations in hostile environments. The influence of occupant position within the aircraft and the use and effectiveness of personal protective equipment could not be effectively analyzed due to a lack of information.

Technological Maturity of Aircraft-Based Methane Sensing for Greenhouse Gas Mitigation.

Methane is a major contributor to anthropogenic greenhouse gas emissions. Identifying large sources of methane, particularly from the oil and gas sectors, will be essential for mitigating climate change. Aircraft-based methane sensing platforms can rapidly detect and quantify methane point-source emissions across large geographic regions, and play an increasingly important role in industrial methane management and greenhouse gas inventory. We independently evaluate the performance of five major methane-sensing aircraft platforms: Carbon Mapper, GHGSat-AV, Insight M, MethaneAIR, and Scientific Aviation. Over a 6 week period, we released metered gas for over 700 single-blind measurements across all five platforms to evaluate their ability to detect and quantify emissions that range from 1 to over 1,500 kg(CH4)/h. Aircraft consistently quantified releases above 10 kg(CH4)/h, and GHGSat-AV and Insight M detected emissions below 5 kg(CH4)/h. Fully blinded quantification estimates for platforms using downward-facing imaging spectrometers have parity slopes ranging from 0.76 to 1.13, with R2 values of 0.61 to 0.93; the platform using continuous air sampling has a parity slope of 0.5 (R2 = 0.93). Results demonstrate that aircraft-based methane sensing has matured since previous studies and is ready for an increasingly important role in environmental policy and regulation.

Observing low-altitude features in ozone concentrations in a shoreline environment via uncrewed aerial systems

Abstract. Ozone is a pollutant formed in the atmosphere by photochemical processes involving nitrogen oxides (NOx) and volatile organic compounds (VOCs) when exposed to sunlight. Tropospheric boundary layer ozone is regularly measured at ground stations and sampled infrequently through balloon, lidar, and crewed aircraft platforms, which have demonstrated characteristic patterns with altitude. Here, to better resolve vertical profiles of ozone within the atmospheric boundary layer, we developed and evaluated an uncrewed aircraft system (UAS) platform for measuring ozone and meteorological parameters of temperature, pressure, and humidity. To evaluate this approach, a UAS was flown with a portable ozone monitor and a meteorological temperature and humidity sensor to compare to tall tower measurements in northern Wisconsin. In June 2020, as a part of the WiscoDISCO20 campaign, a DJI M600 hexacopter UAS was flown with the same sensors to measure Lake Michigan shoreline ozone concentrations. This latter UAS experiment revealed a low-altitude structure in ozone concentrations in a shoreline environment showing the highest ozone at altitudes from 20–100 m a.g.l. These first such measurements of low-altitude ozone via a UAS in the Great Lakes region revealed a very shallow layer of ozone-rich air lying above the surface.

Optimization-Based Control for a Large-Scale Electrical Vertical Take-Off and Landing during an Aircraft’s Vertical Take-Off and Landing Phase with Variable-Pitch Propellers

The UAV industry has witnessed an unprecedented boom in recent years. Among various kinds of UAV platforms, the vertical take-off and landing (VTOL) aircraft with fixed-wing configurations has received more and more attention due to its flexibility and long-distance flying abilities. However, due to the fact that the advance ratio of regular propeller systems during the cruise phase is significantly higher than that during the VTOL phase, a variable-pitch propeller system is proposed and designed which can be applied without additional propulsion mechanisms during both flying stages. Thus, a VTOL aircraft platform is proposed based on the propulsion system constructed of variable-pitch propellers, and appropriate control manners are precisely analyzed, especially during its VTOL phase. As a basic propulsion system, a nonlinear model for variable-pitch propellers is constructed, and an optimization-based control allocation module is developed because of its multi-solution and high-order characteristics. Finally, the objective function is designed according to the stability and energy consumption requirements. Simulation experiments demonstrate that the proposed controller is able to lower energy consumption and maintain the stability of the aircraft while tracking aggressive trajectories for large-scale VTOLs with noises at the same time.

Maximizing the Volume of Collocated Data from Two Coordinated Suborbital Platforms

Abstract Suborbital (e.g., airborne) campaigns that carry advanced remote sensing and in situ payloads provide detailed observations of atmospheric processes, but can be challenging to use when it is necessary to geographically collocate data from multiple platforms that make repeated observations of a given geographic location at different altitudes. This study reports on a data collocation algorithm that maximizes the volume of collocated data from two coordinated suborbital platforms and demonstrates its value using data from the NASA Aerosol Cloud Meteorology Interactions Over the western Atlantic Experiment (ACTIVATE) suborbital mission. A robust data collocation algorithm is critical for the success of the ACTIVATE mission goal to develop new and improved remote sensing algorithms, and quantify their performance. We demonstrate the value of these collocated data to quantify the performance of a recently developed vertically resolved lidar + polarimeter–derived aerosol particle number concentration (Na) product, resulting in a range-normalized mean absolute deviation (NMAD) of 9% compared to in situ measurements. We also show that this collocation algorithm increases the volume of collocated ACTIVATE data by 21% compared to using only nearest-neighbor finding algorithms alone. Additional to the benefits demonstrated within this study, the data files and routines produced by this algorithm have solved both the critical collocation and the collocation application steps for researchers who require collocated data for their own studies. This freely available and open-source collocation algorithm can be applied to future suborbital campaigns that, like ACTIVATE, use multiple platforms to conduct coordinated observations, e.g., a remote sensing aircraft together with in situ data collected from suborbital platforms. Significance Statement This study describes a data collocation (i.e., selection) process that aims to maximize the volume of data identified to be simultaneously collected in time and space from two coordinated measurement platforms. The functional utility of the resultant dataset is also demonstrated by extending the validation of aerosol particle number concentration derived from standard lidar and polarimeter data products from a suborbital mission that used two aircraft platforms.

Influence of Aero-Optical Effect on Laser Communication of Aircraft Platforms

Influence of Aero-Optical Effect on Laser Communication of Aircraft Platforms

De-Striping and De-Smiling of Aerial Hyperspectral Image for Water Color Analysis

Hyperspectral imagery is typically acquired in push-broom mechanism, which is prone to image artifacts such as striping and smile for the sensor array whose sensor elements are not perfectly calibrated. The best practice would be to calibrate the sensor elements before the flight, but post-correction is required when images are already acquired without calibration. While there are some studies that addressed those striping and smile effects for hyperspectral images acquired from satellite or aircraft platforms, few studies were done for hyperspectral images that are focusing water color analysis, where the radiance level is approximately only a tenth of terrestrial scenes. This study proposes a correction method specialized for water scenes that also may contain terrestrial objects together, and analyzes the results using real drone-borne hyperspectral imagery taken for an island area in Korea. The result revealed that the variation in columnar mean before the de-striping, which ranges 5-15%, reduced to under 2% after the correction, also exhibiting successful removal of striping in visual inspection. The smile effect that ranges approximately 1-2 mW/m2/nm/sr, which accounts for 30% of radiance from water area, also reduced to under 0.1 mW/m2/nm/sr after the smile correction.

Synthesizing evidence for the external cycling of NOx in high- to low-NOx atmospheres

External cycling regenerating nitrogen oxides (NOx ≡ NO + NO2) from their oxidative reservoir, NOz, is proposed to reshape the temporal–spatial distribution of NOx and consequently hydroxyl radical (OH), the most important oxidant in the atmosphere. Here we verify the in situ external cycling of NOx in various environments with nitrous acid (HONO) as an intermediate based on synthesized field evidence collected onboard aircraft platform at daytime. External cycling helps to reconcile stubborn underestimation on observed ratios of HONO/NO2 and NO2/NOz by current chemical model schemes and rationalize atypical diurnal concentration profiles of HONO and NO2 lacking noontime valleys specially observed in low-NOx atmospheres. Perturbation on the budget of HONO and NOx by external cycling is also found to increase as NOx concentration decreases. Consequently, model underestimation of OH observations by up to 41% in low NOx atmospheres is attributed to the omission of external cycling in models.

Research on Image Super-Resolution Reconstruction Technology Based on Unsupervised Learning

Affected by the movement of drones, missiles, and other aircraft platforms and the limitation of the accuracy of image sensors, the obtained images have low-resolution and serious loss of image details. Aiming at these problems, this paper studies the image super-resolution reconstruction technology. Firstly, a natural image degradation model based on a generative adversarial network is designed to learn the degradation relationship between image blocks within the image; then, an unsupervised learning residual network is designed based on the idea of image self-similarity to complete image super-resolution reconstruction. The experimental results show that the unsupervised super-resolution reconstruction algorithm is equivalent to the mainstream supervised learning algorithm under ideal conditions. Compared to mainstream algorithms, this algorithm has significantly improved its various indicators in real-world environments under nonideal conditions.

The Microwave Temperature and Humidity Profiler: Description and Preliminary Results.

This manuscript presents the Microwave Temperature and Humidity Profiler (MTHP), a dual-band spectroradiometer designed for measuring multi-incidence angle temperature and humidity atmospheric profiles from an aircraft platform. The MTHP bands are at 60 GHz for measuring the oxygen complex lines, therefore at this band, MTHP has a hyperspectral radiometer able to provide 2048 channels over an 8 GHz bandwidth, and 183 GHz for measuring water vapor, which only uses four channels since this absorption band's spectral richness is simpler. The MTHP builds upon the Microwave Temperature Profiler (MTP) with the inclusion of the hyperspectral radiometer. The instrument's design, components, and calibration methods are discussed in detail, with a focus on the three-point calibration scheme involving internal calibration loads and static air temperature readings. Preliminary results from the Technological Innovation into Iodine and GV aircraft Environmental Research (TI3GER) campaign are presented, showcasing the instrument's performance during flights across diverse geographical regions. The manuscript presents successful antenna temperature measurements at 60 GHz and 183 GHz. The hyperspectral measurements are compared with a simulated antenna temperature using the Atmospheric Radiative Transfer Simulator (ARTS) showing an agreement better than R2 > 0.88 for three of the flights analyzed. Additionally, the manuscript draws attention to potential Radio Frequency Interference (RFI) effects observed during a specific flight, underscoring the instrument's sensitivity to external interference. This is the first-ever airborne demonstration of a broadband and hyperspectral multi-incidence angle 60 GHz measurement. Future work on the MTHP could result in an improved spatial resolution of the atmospheric temperature vertical profile and, hence, help in estimating the Planetary Boundary Layer (PBL) with better accuracy. The MTHP and its hyperspectral multi-incidence angle at 60 GHz have the potential to be a valuable tool for investigating the PBL's role in atmospheric dynamics, offering insights into its impact on Earth's energy, water, and carbon cycles.

A CO2 and H2O Gas Analyzer with Reduced Error due to Platform Motion

Abstract One long-standing technical problem affecting the accuracy of eddy correlation air–sea CO2 flux estimates has been motion contamination of the CO2 mixing-ratio measurement. This sensor-related problem is well known but its source remains unresolved. This report details an attempt to identify and reduce motion-induced error and to improve the infrared gas analyzer (IRGA) design. The key finding is that a large fraction of the motion sensitivity is associated with the detection approach common to most closed- and open-path IRGA employed today for CO2 and H2O measurements. A new prototype sensor was developed to both investigate and remedy the issue. Results in laboratory and deep-water tank tests show marked improvement. The prototype shows a factor of 4–10 reduction in CO2 error under typical at-sea buoy pitch and roll tilts in comparison with an off-the-shelf IRGA system. A similar noise reduction factor of 2–8 is observed in water vapor measurements. The range of platform tilt motion testing also helps to document motion-induced error characteristics of standard analyzers. Study implications are discussed including findings relevant to past field measurements and the promise for improved future flux measurements using similarly modified IRGA on moving ocean observing and aircraft platforms.

A Modified Aeromagnetic Compensation Method Robust to the Motion State of Aviation Platform Part

Aeromagnetic compensation is a signal-processing method to suppress the magnetic interference from the airborne platform that far exceeds the target magnetic signal. With the development of measurement technology, the traditional aeromagnetic compensation model in which the motion platform is considered as a rigidly connected whole cannot satisfy the request for high-quality aeromagnetic detection, and the magnetic interference generated by the small relative motion components needs to draw our attention. In this paper, the source of maneuver magnetic interference on the aircraft platform is split into two parts, i.e., the rigidly connected main body part (MBP) and moving part (MP), and their compensation models can be both built by referring to the Tolles–Lawson (TL) model. The key factor in these two models is how to obtain the direction cosine that describe the maneuvering actions of aircraft. In the MBP compensation model, the direction cosine can be directly obtained by the onboard fluxgate magnetometer. However, those in the MP model cannot be directly obtained because there is no any monitoring equipment for it. Therefore, a scheme for calculating the direction cosine of the MP compensation model is proposed. This scheme combines the direction cosine obtained by the onboard fluxgate magnetometer with the relative motion angles. And considering the influence of geomagnetic gradient magnetic interference, its compensation model is brought to form a new aeromagnetic compensation model, herein called the TLGM model. This model is different from the traditional TL model and is nonlinear since the three unknown relative motion angles, so the quantum genetic algorithm (QGA) is introduced to combine with recursive least-squares to estimate those unknowns. Some field experiments were conducted, and the results show that the proposed method reduces the standard deviations and figures of merit by over 42% and 39%, respectively, compared with those using the previous model. Also, the proposed compensation method requires no additional motion monitoring sensors and is more convenient for practical applications.

A Review on Unmanned Aerial Vehicle Remote Sensing: Platforms, Sensors, Data Processing Methods, and Applications

In recent years, UAV remote sensing has gradually attracted the attention of scientific researchers and industry, due to its broad application prospects. It has been widely used in agriculture, forestry, mining, and other industries. UAVs can be flexibly equipped with various sensors, such as optical, infrared, and LIDAR, and become an essential remote sensing observation platform. Based on UAV remote sensing, researchers can obtain many high-resolution images, with each pixel being a centimeter or millimeter. The purpose of this paper is to investigate the current applications of UAV remote sensing, as well as the aircraft platforms, data types, and elements used in each application category; the data processing methods, etc.; and to study the advantages of the current application of UAV remote sensing technology, the limitations, and promising directions that still lack applications. By reviewing the papers published in this field in recent years, we found that the current application research of UAV remote sensing research can be classified into four categories according to the application field: (1) Precision agriculture, including crop disease observation, crop yield estimation, and crop environmental observation; (2) Forestry remote sensing, including forest disease identification, forest disaster observation, etc.; (3) Remote sensing of power systems; (4) Artificial facilities and the natural environment. We found that in the papers published in recent years, image data (RGB, multi-spectral, hyper-spectral) processing mainly used neural network methods; in crop disease monitoring, multi-spectral data are the most studied type of data; for LIDAR data, current applications still lack an end-to-end neural network processing method; this review examines UAV platforms, sensors, and data processing methods, and according to the development process of certain application fields and current implementation limitations, some predictions are made about possible future development directions.

Utilizing Remote Sensing and Data Analytics Techniques to Detect Methane Emissions from the Oil and Gas Industry and Assist with Sustainability Metrics

SummaryThe purpose of this paper is to provide additional information and insights gained on manuscript SPE-209980-MS, accepted for presentation at the 2022 Society of Petroleum Engineers Annual Technical Conference and Exhibition (Esparza et al. 2022).The energy sector has been identified as one of the main contributors to emissions of anthropogenic greenhouse gases. Therefore, sustainability in the sector is mainly associated with the advancement in environmental and social performance across multiple industries. Individual firms, particularly those belonging to the oil and gas (O&G) industry, are now assessed for their environmental, social, and governance (ESG) performance and their impact on climate change. To meet the different key performance indicators (KPIs) for corporate social responsibility (CSR) and ESG, the planning, development, and operation of O&G infrastructure must be conducted in an environmentally responsible way.Today, operators calculate their own emissions, which are typically self-reported annually, usually relying on emission factors to complement the lack of emission measurement data. This paper discusses how methane detection of O&G infrastructure using remote sensing technologies enables operators to detect, quantify, and minimize methane emissions while gaining insights and understanding of their operations via data analytics products. The remote sensing technologies accounted for in this paper are satellite and aerial platforms operating in tandem with data analytics, providing a scheme to support sustainability initiatives through the quantification of some ESG metrics associated with methane emissions. This paper presents examples of measurements at O&G sites taken with satellites and aircraft platforms, providing evidence of methane emissions at the facility level. A discussion of each platform and how they work together is also presented. Additionally, this paper discusses how these data insights can be used to achieve sustainability goals, functioning as a tool for ESG initiatives through the incorporation of analytical models.

Design and Verification of a Large-Scaled Flapping-Wing Aircraft Named “Cloud Owl”

The bionic flapping-wing aircraft has the advantages of high flexibility and strong concealment; however, in the existing flapping-wing aircraft, the platform performance is influenced by the payload capacity, endurance, and durability; additionally, the mission capability is constrained, making it challenging to put into use in real-world scenarios. In response to this issue, this article offers a thorough design approach for a large-span flapping-wing aircraft, focusing on effective flapping wings, effective flapping mechanism design, and enhancement of flapping mechanism reliability, and ultimately realizing the design and verification of a new bionic flapping-wing aircraft with a large wingspan, called “Cloud Owl”. It has a wingspan of 1.82 m and weighs 980 g. The aircraft is capable of autonomous flight and remote control, and it can carry a range of mission-specific equipment. More than 200 flights have been made by “Cloud Owl” so far in Xi’an, Beijing, Tianjin, Tibet, Ganzi, and other places. It has evolved into a flapping-wing aircraft platform with exceptional stability, payload capacity, and long endurance.

Analysis of a tiered top-down approach using satellite and aircraft platforms to monitor oil and gas facilities in the Permian basin

As energy systems transition towards decarbonization, natural gas is expected to play an important role as a cleaner hydrocarbon fuel source to bridge the gap between renewable energy production and increasing energy demand. Regulations aim to reduce methane emissions from natural gas systems to ensure the total environmental impacts of natural gas production and consumption are indeed lesser than for other fossil fuels. GHGSat Inc., has developed a tiered top-down remote sensing approach utilizing satellite and airborne instruments to monitor methane emissions from industrial sites globally. This satellite-aircraft hybrid system was demonstrated in the Permian basin for detecting and quantifying methane emissions from oil and gas (O&G) facilities. A heavy-tail distribution of methane emissions was observed, with 12% of emitting targets (total sample size of 106) accounting for over 50% of total detected methane emissions. Traditional leak detection and repair (LDAR) programs often incorporate multiple annual screening campaigns with ground-based optical gas imaging (OGI) technologies to detect methane leaks from O&G infrastructure. Three alternative LDAR programs incorporating GHGSat's satellite and airborne monitoring technologies were modelled using the Arolytics AroFEMP methane model. Model parameters were derived from GHGSat's 2021 Permian basin data to evaluate their equivalency and costs against traditional LDAR monitoring. When compared to the required practice of performing OGI surveys four times per year, the proposed alternative LDAR programs were modelled to have at least equivalent methane reduction performance while being substantially more cost-effective.

High-precision angle adaptive control simulation of synchronous motor for automatic lifting and boarding equipment of aircraft platform

In order to improve the accuracy and adaptability of the Angle control of the aircraft platform automatic lifting and boarding synchronous motors, the high precision Angle adaptive control method of the aircraft platform automatic lifting and boarding synchronous motors is studied. The structure and function of lifting mechanism in automatic lifting and boarding device of aircraft platform are analyzed. The mathematical equation of synchronous motor in automatic lifting and boarding device is established in a coordinate system, the ideal transmission ratio of synchronous motor angle is calculated, and the PID control law is designed according to the transmission ratio. Finally, the high precision Angle adaptive control of the synchronous motor of the aircraft platform automatic lifting and boarding device is realized by using the control rate. The simulation results show that the proposed method can quickly and accurately realize the angular position control of the research object, and the control error is within ± 0.15rd, which has high adaptability.