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NASA NTRSDate not supplied

Porosity Prediction and Detection During Composite Cure Using Simulation and Ultrasonic In-Situ Inspection Inside and Autoclave

Composite materials offer unique benefits in aerospace applications such as increased strength-to-weight ratio and improved fatigue properties. They are increasingly being used in major commercial aircraft programs. However, current processing methods can lead to defects in composite parts, which are currently identified using post-manufacturing inspection methods. A cure defects process model has been developed to predict the formation of manufacturing defects (e.g., porosity and fiber waviness) in composites based on the cure parameters and part geometry. However, a capability to directly validate porosity during cure did not exist. Validation methods included comparing resin pressure measured during cure with predictions by the process model and inspection/microscopy after cure. This study developed a high-temperature ultrasonic inspection system to detect porosity defects in composites during autoclave cure and experimentally verify the predictions of the model. The system operated inside an autoclave within an enclosure cooled by intermittent liquid nitrogen(LN2) injections. A high-temperature 2.25 MHz ultrasonic transducer was utilized to transmit ultrasonic waves through the tool plate and into the composite material and to measure the amplitude and time of flight of the reflected waves with a 1 mm × 1 mm resolution. Porosity was observed via the ultrasonic reflections, which experienced increased attenuation in regions of high porosity. Distinct regions of increased porosity were present due to uneven pressure across the panel, which was driven by an intentional misfit between the flat caul plate and the tapered composite panel with ply drops. These observations matched the predictions of the model using the inputs from the experiment (e.g., part material and geometry, cure cycle) and were validated by post-cure ultrasonic inspection and micrographs. The in-situ inspection system was able to successfully provide defect detection and localization and can be applied to future manufacturing of composite structure for aerospace applications.

Porosity↗

NASA NTRS2021

A Study into Validating a Coupled Method of Characteristics and Direct Simulation Monte Carlo Method Against Empirical Data

The following will outline the methodology and results of validating a coupled Method of Characteristics (MOC) and Direct Simulation Monte Carlo (DSMC) method. This research focused specifically on modeling plume impingement, induced by Reaction Control System (RCS) thrusters that flew on the National Aeronautics and Space Administration’s (NASA’s) space shuttle Discovery. For each simulation, the continuum portion of the RCS thruster was simulated using MOC for solving hyperbolic Partial Differential Equations (PDEs) and computed with the NASA code, Reacting and Multi-phase Program (RAMP). The solution was then implemented as a starting condition into the NASA DSMC code, Direct Simulation and Monte Carlo Analysis Code (DAC). Typically, DSMC models rely on code-to-code validation for fidelity. The significance of this research is in its ability to validate its models against empirical data. Prior to computing solutions for these simulations, the mesh size and structure were optimized and many variants of DSMC input parameters were iterated on in order to acquire a reliable, mesh-independent, fully optimized numerical solution. This research will discuss the mathematical formulation of MOC for nozzle flow and DSMC for rarefied gases. Additionally, it will provide an explanation of how to implement these mathematical concepts into the two solvers: RAMP and DAC. Ultimately, this research will demonstrate that the overall process illustrated produces results in good agreement with empirical data. As a consequence, the methodology presented is granted an increased level of confidence and will greatly contribute to the aerospace industry and its effort in understanding and predicting rarefied flow fields.

Direct Simulation Monte Carlo Analysis Code↗

NASA NTRS2021

A Study into Validating A Coupled Method of Characteristics And Direct Simulation Monte Carlo Method Against Empirical Data

DAC↗

DOE OSTI2025

Summary Report Of The FY25 Computational Fluid Dynamics Verification And Validation Exercises In The Advanced Reactor Technologies - Gas-cooled Reactor Program

Verification and Validation (V&V) of numerical tools is critical for ensuring reasonable predictions during design, safety analysis, and licensing. Recent work in the Advanced Reactor Technologies - Gas-cooled Reactor (ART-GCR) program has focused on V&V of common Computational Fluid Dynamics (CFD) tools that are used within the Untied States. This report presents an update on these CFD V&V activities. These Generation IV Forum (GIF) Very High Temperature Reactor (VHTR) Computational Methods, Validation, and Benchmarking (CMVB) is an international organization dedicated to the verification and validation of High Temperature Gas-Cooled Reactor (HTGR) simulation tools. Participation in the CMVB provides additional value to the V&V activities, as it allows for access to a wider range of data, and provides valuable benchmarking exercises. Three HTGR phenomena are targeted: Reactor Cavity Cooling System (RCCS) performance, core bypass flow, and lower plenum mixing. Simulations of the University of Wisconsin-Madison (UW-Madison) RCCS facilities are performed with Reynolds Averaged Navier-Stokes (RANS) in StarCCM+. Results are compared for both forced and natural convection conditions, with both exhibiting good agreement with experimental measurements. The Idaho National Laboratory (INL) matched index of refraction (MIR) and Korean Atomic Energy Research Institute (KAERI) bypass flow expeirments are used to validation CFD predictions of bypass flow. Simulations are performed with RANS in StarCCM+ and with Large Eddy Simulation (LES) in NekRS. Finally, preliminary simulations of the Institute of Nuclear and New Energy Technology (INET) lower plenum mixing facilities are presented. Initial work has developed models with LES, RANS, and porous media models. These preliminary models are presented and compared to each other to gauge differences in predictions with each of the three methods.

and Benchmarking (CMVB)↗

NASA NTRS2004

Validating the autonomous EO-1 science agent

This paper describes the validation process for the Autonomous Science Agent, a software agent that is currently flying onboard NASA EO-1 spacecraft. The agent autonomously collects, analyzes, and reacts to onboard science data. The Autonomous Science Agent has been designed using a layered architectural approach with specific redundant safeguards to reduce the risk of an agent malfunction to the EO-1 spacecraft. This safe design has been thoroughly validated by informal validation methods supplemented by sub-system and system-level testing. This paper describes the analysis used to define agent safety, elements of the design that increase the safety of the agent, and the process used to validate agent safety.

software↗

DOE OSTI2020

Clinically applicable 53-Gene prognostic assay predicts chemotherapy benefit in gastric cancer: A multicenter study

BACKGROUND:We previously established a 53-gene prognostic signature for overall survival (OS) of gastric cancer patients. This retrospective multi-center study aimed to develop a clinically applicable gene expression detection assay and to investigate the prognostic value of this signature. METHODS:A TCGA gastric adenocarcinoma cohort (TCGA-STAD) was used for comparing 53-gene signature with other gene signatures. A high-throughput mRNA hybridization gene expression assay was developed to quantify the expression of 53-genes in formalin-fixed paraffin-embedded tissues of 540 patients enrolled from three hospitals. 180 patents were randomly selected from two hospitals to build a prognostic prediction model based on the 53-gene signature using leave-p-out (one-third out) cross-validation method together with Cox regression and Kaplan-Meier analysis, and the model was assessed on three validation cohorts. FINDINGS:In the evaluation phase, studies based on TCGA-STAD showed that the 53-gene signature was significantly superior to other three prognostic signatures and was independent of TCGA molecular subtypes and clinical factors. For clinical validation and utility, the prognostic scores were generated using the newly developed assay, which was reliable and sensitive, in 100 sampling training sets and were significantly associated with OS in 100 sampling validation sets. The scores were significantly associated with OS in three independent and combined validation cohorts, and in patients with stages II and III/IV. The multivariate Cox regression demonstrated that the prognostic power of the score was independent of clinical factors, consistent with those findings in the TCGA dataset. Finally, patients with good prognostic scores exhibited significantly a better 5-year OS rate from adjuvant FOLFOX chemotherapy after surgery than from other chemotherapies. INTERPRETATION:The 53-gene prognostic score system is clinically applicable for predicting the OS of patients independent of clinical factors in gastric cancers, which could also be a promising predictive biomarker for FOLFOX regimen. FUNDING:Chinese National Science and Technology, National Natural Science Foundation and Natural Science Foundation of Jiangsu Province.

60 APPLIED LIFE SCIENCES↗

NASA NTRS1990

Knowledge-based system verification and validation

The objective of this task is to develop and evaluate a methodology for verification and validation (V&V) of knowledge-based systems (KBS) for space station applications with high reliability requirements. The approach consists of three interrelated tasks. The first task is to evaluate the effectiveness of various validation methods for space station applications. The second task is to recommend requirements for KBS V&V for Space Station Freedom (SSF). The third task is to recommend modifications to the SSF to support the development of KBS using effectiveness software engineering and validation techniques. To accomplish the first task, three complementary techniques will be evaluated: (1) Sensitivity Analysis (Worchester Polytechnic Institute); (2) Formal Verification of Safety Properties (SRI International); and (3) Consistency and Completeness Checking (Lockheed AI Center). During FY89 and FY90, each contractor will independently demonstrate the user of his technique on the fault detection, isolation, and reconfiguration (FDIR) KBS or the manned maneuvering unit (MMU), a rule-based system implemented in LISP. During FY91, the application of each of the techniques to other knowledge representations and KBS architectures will be addressed. After evaluation of the results of the first task and examination of Space Station Freedom V&V requirements for conventional software, a comprehensive KBS V&V methodology will be developed and documented. Development of highly reliable KBS's cannot be accomplished without effective software engineering methods. Using the results of current in-house research to develop and assess software engineering methods for KBS's as well as assessment of techniques being developed elsewhere, an effective software engineering methodology for space station KBS's will be developed, and modification of the SSF to support these tools and methods will be addressed.

Johnson, Sally C.↗

NASA NTRSDate not supplied

Tailoring the Stiffness of Large Mirrors to Reduce Specific Optical Aberrations

Presented is a method that tailors the geometry of a mirror’s core structure as well as the mounting interface such that a desired set of aberrations is reduced. It will be shown that targeting specific aberrations as opposed to reducing overall surface figure error (SFE) is a valid method to reduce weight or improve performance. Analyzed first is the self-weight deflection of a thin circular plate of uniform thickness continuously supported along its outer edge. The Kirchhoff-Love plate bending equations are related to the radially symmetric Zernike polynomials of piston, defocus, and primary spherical aberration. Next, the mirror’s radial thickness is optimized to eliminate primary and secondary spherical aberrations when the outer edge is simply supported. As an example, the method is demonstrated using a 2-meter diameter aluminum mirror where surface deflections can have an appreciable effect at mid-to-near infrared wavelengths

mirror stiffness optimization↗

DOE OSTI2024

Spin-Controllable Dynamics in Defect-Engineered Carbon Nanotubes as Single Photon Emitters: Data-Driven Modeling and Computations

Quantum technologies, such as quantum computing and sensing, require efficient single-photon emission (SPE) sources that operate at room temperature in telecom wavelengths. While several materials can serve as SPE sources, no single platform meets all the criteria for efficiency, ambient operation, and scalability. Single-walled carbon nanotubes (SWCNTs) with covalently attached molecules offer a promising solution. Their SPE can be easily tuned via modifications of the SWCNT's diameter, chirality, and bonded molecules, enabling emission across near-IR to telecom wavelengths at ambient conditions. However, to fully realize the potential of SWCNTs and unlock their quantum capabilities, a deeper understanding of how structural defects from molecular adducts affect their emission and competing photoexcited processes is essential. To address this gap in our knowledge, this project combined quantum chemistry calculations with data-driven methods of cheminformatics (QSAR) and machine learning (ML). The developed computational approaches have provided several design strategies for covalent functionalization of SWCNTs to improve their optical response. The collaboration with Los Alamos National Lab (LANL) enabled direct comparison of computational and experimental data, facilitating method validation. This partnership was enhanced through access to LANL's Center for Integrated Nanotechnologies (CINT) utilizing User Facility Program and summer internships, which provided three NDSU graduate students with hands-on experience at LANL. The outcomes of this project included (1) Advancing the current stage of computational methods in accurate modeling of non-adiabatic spin-dependent photoexcited dynamics and its applicability to nanosystems consisting of thousands of atoms, realized as open-access codes linked to existing DFT-based software; (2) Establishing the relationship between the structure of adducts and SWCNTs and intrinsic excitonic and spin properties of defect states for guiding novel synthetic strategies and experimental probes of chemically functionalized SWCNTs as near-IR emitting materials; (3) Generating virtual libraries of hypothetical functionalized SWCNTs for virtual screening of their chemical structures and optical properties, leveraging new functionalities of SWCNTs; (4) Offering a unique experience for NDSU graduate students that prepared them for future scientific careers related to materials modeling and big data processing. These results were summarized in 12 published journal papers and 3 recently submitted papers. One of a key finding is that the position of defect sites on the SWCNT surface primarily drives the emission redshift (up to 100 meV), while the polarity of the defect-inducing molecules has a much smaller effect (~10 meV). However, the electron-donating or withdrawing properties of a molecule influence selecting reactivity of defect sites. These insights important for optimizing synthetic protocols for desired emissions in SWCNTs. We also revealed that the interaction between two defects at various positions on the SWCNT enhances the redshift and optical activity of states, favoring strong near-IR emission. This suggests that manipulations in defect concentrations is a promising strategy for controlling efficient emission. Mostly important, the defect position was found controllable by the spin states of photoexcited intermediates: Excited aromatic molecules form ortho defects with SWCNTs at their singlet states in the presence of oxygen, while oxygen-free conditions favor para defects via the triplet-state mechanism. Additionally, a heat-activated [2+2] cycloaddition reaction facilitates divalent defect formation with fewer bonding positions that narrows emission bands. These groundbreaking findings have been experimentally validated and significantly advance our understanding of defect chemistry in SWCNTs. Using a novel encoding technique and 3D-MoRSE descriptors, we developed highly accurate ML/QSAR models to predict both the 3D structure and optical properties of SWCNTs with chemical defects. This model enabled the creation of a virtual library of 125,556 structures, providing new insights into the relationship between SWCNT-defect structure and emission.

77 NANOSCIENCE AND NANOTECHNOLOGY↗

DOE OSTI2021

A Machine Learning-based Reliability Evaluation Model for Integrated Power-Gas Systems

This article proposes a hybrid machine learning method for the reliability evaluation of integrated power-gas systems (IPGS) under the uncertain component failure probability distributions. The Random Forest (RF) method is designed to select important features to solve the insufficient quantity of data and the curse of dimensionality problems. The Extreme Gradient Boosting (XGBoost) regression algorithm is developed to quantify the relationship between the uncertain parameters and reliability metrics. Moreover, a ten-fold cross-validation method is employed to further improve the accuracy of the regression model. Simulation results on three test systems show that the proposed method can achieve high accuracy for the reliability evaluation.

24 POWER TRANSMISSION AND DISTRIBUTION↗

NASA NTRS2005

IEEE/NASA Workshop on Leveraging Applications of Formal Methods, Verification, and Validation

This volume contains the Preliminary Proceedings of the 2005 IEEE ISoLA Workshop on Leveraging Applications of Formal Methods, Verification, and Validation, with a special track on the theme of Formal Methods in Human and Robotic Space Exploration. The workshop was held on 23-24 September 2005 at the Loyola College Graduate Center, Columbia, MD, USA. The idea behind the Workshop arose from the experience and feedback of ISoLA 2004, the 1st International Symposium on Leveraging Applications of Formal Methods held in Paphos (Cyprus) last October-November. ISoLA 2004 served the need of providing a forum for developers, users, and researchers to discuss issues related to the adoption and use of rigorous tools and methods for the specification, analysis, verification, certification, construction, test, and maintenance of systems from the point of view of their different application domains.

Margaria, Tiziana↗

DOE OSTI2020

Advancing Offshore Wind Resource Characterization Using Buoy-based Observations

As countries continue to implement sustainable and renewable energy goals, the need for affordable low-carbon technologies, including those related to offshore wind energy, is accelerating. The U.S. federal government recognizes the environmental and economic benefits of offshore wind development and is taking the necessary steps to overcome critical challenges facing the industry to realize these benefits. The U.S. Department of Energy (DOE) is investing in buoy-mounted lidar systems to facilitate offshore measurement campaigns that will advance our understanding of the offshore environment and provide the observational data needed for model validation, particularly at hub height where offshore observations are particularly lacking. On behalf of the DOE, Pacific Northwest National Laboratory manages a Lidar Buoy Program that facilitates meteorological and oceanographic data collection using validated methods to support the U.S. offshore wind industry. Since being acquired in 2014, two DOE lidar buoys have been deployed on the U.S. east and west coasts; and their data represent the first publicly available multi-seasonal hub height data to be collected in U.S. waters. In addition, the buoys have undergone performance testing, significant upgrades, and a lidar validation campaign to ensure the accuracy and reliability of the lidar data needed to support wind resource characterization and model validation. The Lidar Buoy Program is providing valuable offshore data to the wind energy community, while focusing data collection on areas of acknowledged high priority.

offshore wind energy, lidar buoy, wind resource ch↗

DOE OSTI2022

Construction of Women’s All-Around Speed Skating Event Performance Prediction Model and Competition Strategy Analysis Based on Machine Learning Algorithms

Introduction Accurately predicting the competitive performance of elite athletes is an essential prerequisite for formulating competitive strategies. Women’s all-around speed skating event consists of four individual subevents, and the competition system is complex and challenging to make accurate predictions on their performance. Objective The present study aims to explore the feasibility and effectiveness of machine learning algorithms for predicting the performance of women’s all-around speed skating event and provide effective training and competition strategies. Methods The data, consisting of 16 seasons of world-class women’s all-around speed skating competition results, used in the present study came from the International Skating Union (ISU). According to the competition rules, distinct features are filtered using lasso regression, and a 5,000 m race model and a medal model are built using a fivefold cross-validation method. Results The results showed that the support vector machine model was the most stable among the 5,000 m race and the medal models, with the highest AUC (0.86, 0.81, respectively). Furthermore, 3,000 m points are the main characteristic factors that decide whether an athlete can qualify for the final. The 11th lap of the 5,000 m, the second lap of the 500 m, and the fourth lap of the 1,500 m are the main characteristic factors that affect the athlete’s ability to win medals. Conclusion Compared with logistic regression, random forest, K-nearest neighbor, naive Bayes, neural network, support vector machine is a more viable algorithm to establish the performance prediction model of women’s all-around speed skating event; excellent performance in the 3,000 m event can facilitate athletes to advance to the final, and athletes with outstanding performance in the 500 m event are more likely competitive for medals.

Liu, Meng↗

NASA NTRS1977

A generalized vortex lattice method for subsonic and supersonic flow applications

If the discrete vortex lattice is considered as an approximation to the surface-distributed vorticity, then the concept of the generalized principal part of an integral yields a residual term to the vorticity-induced velocity field. The proper incorporation of this term to the velocity field generated by the discrete vortex lines renders the present vortex lattice method valid for supersonic flow. Special techniques for simulating nonzero thickness lifting surfaces and fusiform bodies with vortex lattice elements are included. Thickness effects of wing-like components are simulated by a double (biplanar) vortex lattice layer, and fusiform bodies are represented by a vortex grid arranged on a series of concentrical cylindrical surfaces. The analysis of sideslip effects by the subject method is described. Numerical considerations peculiar to the application of these techniques are also discussed. The method has been implemented in a digital computer code. A users manual is included along with a complete FORTRAN compilation, an executed case, and conversion programs for transforming input for the NASA wave drag program.

Miranda, L. R.↗

NASA NTRS2001

Follow That Satellite: EO-1 Maneuvers into Closed Formation With Landsat-7

As the Landsat-7 spacecraft continued NASA's historic program of earth imaging, begun over three decades ago, NASA launched the Earth Observing-1 (EO-1) spacecraft carrying examples of the next generation of Landsat-7 instruments. The validation method for these instruments was to have EO-1 fly in a close formation behind Landsat-7 on the same World Reference System path. From that formation hundreds of near coincident images would be taken by each spacecraft and compared to evaluate improvements in the EO-1 instruments. This paper will address the mission analysis required to launch and maneuver EO-1 into the formation with Landsat-7 where instrument validation was to occur plus a summary of completing the formation acquisition. EO-1 is required to operate one minute +/- 6 seconds behind Landsat-7 during the period of co-fly imaging with a cross track separation of within + 3 kilometers. This separation time can also be stated as a one minute +/- 6 seconds time difference in the Mean Local Time (MLT) at the descending nodes. Achieving the required MLT is heavily dependent on the time of launch. The EO-1 launch window, which had to accommodate the dual payloads of EO-1 and SAC-C, was very limited ranging from 0 to 22 seconds over the 16 day Landsat-7 WRS repeat cycle during which EO-1 was launched. Each EO-1 launch opportunity that occurred on a different day of a Landsat-7 16 day repeat cycle required a separate and distinct maneuver profile. These profiles varied significantly in duration and amount of onboard propellant required to achieve them. EO-1 launched on a day judged to have "medium" resource requirements for achieving the formation with Landsat-7. To phase EO-1 one minute behind Landsat-7 in the along track direction, a series of altitude adjusts separated by specific drift intervals were executed. Additional maneuvers slightly changed the EO-1 inclination to maintain the MLT requirements. Orbit maneuvers were planned and executed within errors of less than 1.5 percent and propellant usage was near nominal consuming 3.4 kilograms out of a launch and early orbit budget of 11 kilograms. The pre-launch 3 -sigma propellant budget allowed for 1+ years of EO-1 mission life. The success of the EO-1 launch and early orbit operations provided sufficient propellant for nearly 4 years of on orbit operations. Special action taken during the EO-1 maneuver period involved some maneuver re-planning to reduce concerns about a potential close approach between EO-1 and Landsat-7. The result of this re-planning was a safer close approach and improvement in future formation acquisition planning.

DeFazio, Robert↗

NASA NTRS2001

Follow That Satellite: EO-1 Maneuvers Into Close Formation With Landsat-7

As the Landsat-7 (LS-7) spacecraft continued NASA's historic program of earth imaging begun over three decades ago, NASA launched the Earth Observing-1 (EO-1) spacecraft carrying examples of the next generation of LS instruments. The validation method for these instruments was to have EO-1 fly in a close formation behind LS-7 on the same World Reference System (WRS) path. From that formation hundreds of near-coincident images would be taken by each spacecraft and compared to evaluate improvements in the EO-1 instruments. This paper will address the mission analysis required to launch and maneuver EO-1 into the formation with LS-7 where instrument validation was to occur plus a summary of completing the formation acquisition. Each EO-1 launch opportunity that occurred on a different day of a LS-7 16-day repeat cycle required a separate and distinct maneuver profile.

DeFazio, Robert L.↗

NASA NTRSDate not supplied

A Physics-Based Spatial Wake Interactional Model of Fixed-Wing Aircraft and Rotorcraft for Urban Air Mobility

This paper presents a study of a physics-based spatial wake interactional model for urban air mobility. A modeling method for spatial wake interaction of fixed-wing aircraft and rotorcraft is presented. The method validates an existing wake vortex model with flight data from the existing literature. The model is then adopted for both fixed-wing aircraft and rotorcraft. A lift circulation model is developed for rotorcraft to account for unsteady aerodynamics and the compressibility effect. This lift circulation model provides more realistic estimate of lift circulation for rotorcraft for used in wake vortex modeling. A vehicle-building wake interaction is studied using the method of image. The effects of wake vortex encounters on aerodynamic loads, stability, and control are examined. A flight control simulation is performed to demonstrate recovery during a simulated wake vortex encounter.

Wake Vortex Encounter↗

NASA NTRS2013

Modeling Weather Impact on Airport Arrival Miles-in-Trail Restrictions

When the demand for either a region of airspace or an airport approaches or exceeds the available capacity, miles-in-trail (MIT) restrictions are the most frequently issued traffic management initiatives (TMIs) that are used to mitigate these imbalances. Miles-intrail operations require aircraft in a traffic stream to meet a specific inter-aircraft separation in exchange for maintaining a safe and orderly flow within the stream. This stream of aircraft can be departing an airport, over a common fix, through a sector, on a specific route or arriving at an airport. This study begins by providing a high-level overview of the distribution and causes of arrival MIT restrictions for the top ten airports in the United States. This is followed by an in-depth analysis of the frequency, duration and cause of MIT restrictions impacting the Hartsfield-Jackson Atlanta International Airport (ATL) from 2009 through 2011. Then, machine-learning methods for predicting (1) situations in which MIT restrictions for ATL arrivals are implemented under low demand scenarios, and (2) days in which a large number of MIT restrictions are required to properly manage and control ATL arrivals are presented. More specifically, these predictions were accomplished by using an ensemble of decision trees with Bootstrap aggregation (BDT) and supervised machine learning was used to train the BDT binary classification models. The models were subsequently validated using data cross validation methods. When predicting the occurrence of arrival MIT restrictions under low demand situations, the model was able to achieve over all accuracy rates ranging from 84% to 90%, with false alarm ratios ranging from 10% to 15%. In the second set of studies designed to predict days on which a high number of MIT restrictions were required, overall accuracy rates of 80% were achieved with false alarm ratios of 20%. Overall, the predictions proposed by the model give better MIT usage information than what has been currently provided under current day operations. Traffic flow managers can use these predictions to identify potential MIT restrictions to eliminate (e.g., those occurring during low arrival demand periods), and to determine the days in which a significant number of restrictions may be required

Operation↗