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Search indexed NASA NTRS and DOE OSTI research on propulsion, heat transfer, battery materials and energy systems. Follow report and document links to the original sources.

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All sourcesNASA NTRSDOE OSTI
DOE OSTI2023

Several Small or Single Large? Quantifying the Catchment-Wide Performance of On-Site Wastewater Treatment Plants with Inaccurate Sensors

On-site wastewater treatment plants (OSTs) often lack monitoring, resulting in unreliable treatment performance. They thus appear to be a stopgap solution despite their potential contribution to circular water management. Low-maintenance but inaccurate soft sensors are emerging that address this concern. However, how their inaccuracy impacts the catchment-wide treatment performance of a system of many OSTs has not been quantified. Here, we develop a stochastic model to estimate catchment-wide OST performances with a Monte Carlo simulation. In our study, soft sensors with a 70% accuracy improved the treatment performance from 66% of the time functional to 98%. Soft sensors optimized for specificity, indicating the true negative rate, improve the system performance, while sensors optimized for sensitivity, indicating the true positive rate, quantify the treatment performance more accurately. This new insight leads us to suggest programming two soft sensors in practical settings with the same hardware sensor data as input: one soft sensor geared to high specificity for maintenance scheduling and one geared to high sensitivity for performance quantification. Our findings suggest that a maintenance strategy combining inaccurate sensors with appropriate alarm management can vastly improve the mean catchment-wide treatment performance of a system of OSTs.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2013

Improvements, enhancements, and optimizations of COBRA-TF

The Reactor Dynamics and Fuel Management Group (RDFMG) at The Pennsylvania State University (PSU) has become active in the Consortium for Advanced Simulation of Light Water Reactors (CASL) program by delivering, supporting, and further developing CTF, the PSU version of the Coolant Boiling in Rod Arrays - Two Fluids (COBRA-TF) Thermal/Hydraulic (T/H), sub-channel program. New development work on CTF was primarily geared towards decreasing the execution time of the code so that it may eventually be used for performing pin-by-pin, full-core simulations. Great gains have been made through targeting sections of source code for optimization. For example, wall clock time has been reduced for a one-assembly, three-dimensional model, containing {approx}9,400 mesh cells, from 9.2 min to 1 min. A further improvement has been reduction in code memory usage, which was previously prohibitive for large models. In conjunction with the run time speedups, this has enabled the simulation of a refined quarter-core model ({approx}460,000 mesh cells), which saw a reduction in memory usage from over 130 GB to less than 3 GB. In addition to the optimization work, RDFMG has also created a preprocessor utility for the fast and less error-prone generation of CTF input decks. Furthermore, basic post-processing capabilities have been implemented by creating a CTF subroutine for producing Visualization Tool-Kit (VTK) files that output mesh data and associated simulation results. These VTK files can be opened with visualization software. (authors)

97 MATHEMATICS AND COMPUTING↗
NASA NTRS2022

Assimilation of NASA’s Airborne Snow Observatory Snow Measurements for Improved Hydrological Modeling: A Case Study Enabled by the Coupled LIS/WRF-Hydro System

he NASA LIS/WRF-Hydro system is a coupled modeling framework that combines the modeling and data assimilation (DA) capabilities of the NASA Land Information System (LIS) with the multi-scale surface hydrological modeling capabilities of the WRF-Hydro model, both of which are widely used in both operations and research. This coupled modeling framework builds on the linkage between land surface models (LSMs), which simulate surface boundary conditions in atmospheric models, and distributed hydrologic models, which simulate horizontal surface and sub-surface flow, adding new land DA capabilities. In the present study, we employ this modeling framework in the Tuolumne River basin in central California. We demonstrate the added value of the assimilation of NASA Airborne Snow Observatory (ASO) snow water equivalent (SWE) estimates in the Tuolumne basin. This analysis is performed in both LIS as an LSM column model and LIS/WRF-Hydro, with hydrologic routing. Results demonstrate that ASO DA in the basin reduced snow bias by as much as 30% from an open-loop (OL) simulation compared to three independent datasets. It also reduces downstream streamflow runoff biases by as much as 40%, and improves streamflow skill scores in both wet and dry years. Analysis of soil moisture and evapotranspiration (ET) also reveals the impacts of hydrologic routing from WRF-Hydro in the simulations, which would otherwise not be resolved in an LSM column model. By demonstrating the beneficial impact of SWE DA on the improving streamflow forecasts, the article outlines the importance of such observational inputs for reservoir operations and related water management applications.

Hydrologic modeling↗
NASA NTRS2011

An Interim Report on NASA's Draft Space Technology Roadmaps

NASA has developed a set of 14 draft roadmaps to guide the development of space technologies under the leadership of the NASA Office of the Chief Technologist (OCT). Each of these roadmaps focuses on a particular technology area (TA). The roadmaps are intended to foster the development of advanced technologies and concepts that address NASA's needs and contribute to other aerospace and national needs. OCT requested that the National Research Council conduct a study to review the draft roadmaps, gather and assess relevant community input, and make recommendations and suggest priorities to inform NASA's decisions as it finalizes its roadmaps. The statement of task states that "based on the results of the community input and its own deliberations, the steering committee will prepare a brief interim report that addresses high-level issues associated with the roadmaps, such as the advisability of modifying the number or technical focus of the draft NASA roadmaps." This interim report, which does not include formal recommendations, addresses that one element of the study charge. NASA requested this interim report so that it would have the opportunity to make an early start in modifying the draft roadmaps based on feedback from the panels and steering committee. The final report will address all other tasks in the statement of task. In particular, the final report will include a prioritization of technologies, will describe in detail the prioritization process and criteria, and will include specific recommendations on a variety of topics, including many of the topics mentioned in this interim report. In developing both this interim report and the final report to come, the steering committee draws on the work of six study panels organized by technical area, loosely following the organization of the 14 roadmaps, as follows: A Panel 1: Propulsion and Power TA01 Launch Propulsion Systems TA02 In-Space Propulsion Technologies TA03 Space Power and Energy Storage Systems TA13 Ground and Launch Systems Processing B Panel 2: Robotics, Communications, and Navigation TA04 Robotics, TeleRobotics, and Autonomous Systems TA05 Communication and Navigation Systems C Panel 3: Instruments and Computing TA08 Science Instruments, Observatories, and Sensor Systems TA11 Modeling, Simulation, Information Technology, and Data Processing D Panel 4: Human Health and Surface Exploration TA06 Human Health, Life Support, and Habitation Systems TA07 Human Exploration Destination Systems E Panel 5: Materials Panel TA10 Nanotechnology TA12 Materials, Structures, Mechanical Systems, and Manufacturing TA14 Thermal Management Systems F Panel 6: Entry, Descent, and Landing Panel TA09 Entry, Descent, and Landing Systems In addition to drawing on the expertise represented on the steering committee and panels, the committee obtained input from each of 14 public workshops held on each of the 14 roadmaps. At these 1-day workshops, invited speakers, guests, and members of the public engaged in discussions on the different technology areas and their value to NASA. Broad community input was also solicited from a public website, where more than 240 public comments were received on the draft roadmaps in response to application of criteria (such as benefit, risk and reasonableness, and alignment with NASA and national goals) that the steering committee established. This interim report reflects the results of deliberations by the steering committee in light of these public inputs as well as additional inputs from the six panels. The steering committee's final report will be completed early in 2012. That report will prioritize the technologies that span the entire scope of the 14 roadmaps and provide additional guidance on crosscutting themes and other relevant topics.

Source record↗
DOE OSTI2021

Nuclear Materials Process Modeling at the Y-12 National Security Complex

The Y-12 National Security Complex (Y-12) has implemented process modeling for various accountable nuclear materials operations that are performed throughout the plant. Using a discrete, event-based dynamic simulation program, key nuclear material streams are modeled, allowing Y-12 to effectively manage numerous points of interest within the plant’s production operations. Integration of the various material processes into a single, interdependent supply and demand model is one of the ongoing focuses within Y-12’s process modeling effort. The primary purpose of using dynamic simulation modeling is to allow for analysis of the nuclear materials inventories and forecasted supplies based on future demands. Analysis of these inventories includes capacity evaluation, bottleneck mitigation, and assessments of individual pieces of equipment to inform future facility investment decisions and associated project schedules. Modeling of the nuclear materials processes throughout the complex also allows for incorporation of changes relevant to production capabilities such as the upcoming transition of specific operations to the new Uranium Processing Facility. Prior to implementation of process modeling, Y-12 forecasted supply and demand of accountable nuclear materials streams using Microsoft Excel. With deterministic models such as Microsoft Excel, the annual forecasts, generated within data input condition parameters, can only provide a fixed point of data. Fixed data cannot simulate integrated material streams and account for the possibility of occurrences and other changes that dynamic simulations take into consideration. Y-12’s dynamic process modeling allows integrated simulations of multiple accountable nuclear materials processes, including supply and demand forecasting and analysis, and is a coordinated effort involving many steps of verification and validation (V&V), site briefings, testing, reporting, data mining, planning, and documentation that spans various programs throughout the Y-12 complex.

12 MANAGEMENT OF RADIOACTIVE AND NON-RADIOACTIVE W↗
DOE OSTI2024

Modeling the Effects of Artificial Drainage on Agriculture-dominated Watersheds using a Fully Distributed Integrated Hydrology Model: Datasets, scripts, model files

This model-data archive supports the research paper that demonstrates the integration of agricultural drainage features—specifically, narrow engineered ditches and tile drains—into a fully distributed, basin-scale integrated surface-subsurface hydrology model (ISSHM), Amanzi-ATS. The model employs innovative computational meshes aligned with agricultural ditches and incorporates the physically based Hooghoudt's drainage equation to simulate tile drainage, offering a novel strategy that enhances the accuracy of hydrological simulations.The archived dataset includes input parameters, model configurations, and select simulation outputs for the Amanzi-ATS model that successfully captured the streamflow patterns in the Portage River Watershed as validated by USGS gauge readings. Jupyter notebook for the preparation of model inputs and post-processing of outputs are also included. The model's predictive performance achieved a normalized Kling-Gupta Efficiency (KGE) of 0.81, surpassing SWAT without the necessity for site-specific calibration.The Amanzi-ATS model presented in this modeL-data archive allows for numerical experiments to explore the shifts in the flow structure under different drainage scenarios. As a tool for advancing the understanding of distributed hydrological responses and nutrient cycling, this archived model provides valuable insights for researchers, modelers, and decision-makers involved in watershed management and environmental modeling.The Watershed Workflow package is implemented in Python3. The Jupyter notebooks can be executed through multiple open-source tools, for example, Anaconda Jupyter Lab, VS Studio Code, etc. Other data files include CSV and HDF5 files, which can be read through Python scripts. The input files for the ATS model, open-source integrated hydrology, and transport model, are in XML format and can be edited in any commonly used text editors.

54 ENVIRONMENTAL SCIENCES↗
NASA NTRS1990

Simulator comparison of thumball, thumb switch, and touch screen input concepts for interaction with a large screen cockpit display format

A piloted simulation study was conducted comparing three different input methods for interfacing to a large screen, multiwindow, whole flight deck display for management of transport aircraft systems. The thumball concept utilized a miniature trackball embedded in a conventional side arm controller. The multifunction control throttle and stick (MCTAS) concept employed a thumb switch located in the throttle handle. The touch screen concept provided data entry through a capacitive touch screen installed on the display surface. The objective and subjective results obtained indicate that, with present implementations, the thumball concept was the most appropriate for interfacing with aircraft systems/subsystems presented on a large screen display. Not unexpectedly, the completion time differences between the three concepts varied with the task being performed, although the thumball implementation consistently outperformed the other two concepts. However, pilot suggestions for improved implementations of the MCTAS and touch screen concepts could reduce some of these differences.

Jones, Denise R.↗
DOE OSTI2019

Unifying soil organic matter formation and persistence frameworks: the MEMS model

Soil organic matter (SOM) dynamics in ecosystem-scale biogeochemical models have traditionally been simulated as immeasurable fluxes between conceptually defined pools. This greatly limits how empirical data can be used to improve model performance and reduce the uncertainty associated with their predictions of carbon (C) cycling. Recent advances in our understanding of the biogeochemical processes that govern SOM formation and persistence demand a new mathematical model with a structure built around key mechanisms and biogeochemically relevant pools. Here, we present one approach that aims to address this need. Our new model (MEMS v1.0) is developed from the Microbial Efficiency-Matrix Stabilization framework, which emphasizes the importance of linking the chemistry of organic matter inputs with efficiency of microbial processing and ultimately with the soil mineral matrix, when studying SOM formation and stabilization. Building on this framework, MEMS v1.0 is also capable of simulating the concept of C saturation and represents decomposition processes and mechanisms of physico-chemical stabilization to define SOM formation into four primary fractions. After describing the model in detail, we optimize four key parameters identified through a variance-based sensitivity analysis. Optimization employed soil fractionation data from 154 sites with diverse environmental conditions, directly equating mineral-associated organic matter and particulate organic matter fractions with corresponding model pools. Finally, model performance was evaluated using total topsoil (0–20 cm) C data from 8192 forest and grassland sites across Europe. Despite the relative simplicity of the model, it was able to accurately capture general trends in soil C stocks across extensive gradients of temperature, precipitation, annual C inputs and soil texture. The novel approach that MEMS v1.0 takes to simulate SOM dynamics has the potential to improve our forecasts of how soils respond to management and environmental perturbation. Ensuring these forecasts are accurate is key to effectively informing policy that can address the sustainability of ecosystem services and help mitigate climate change.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2022

Control Oriented Model of Cabin-HVAC System in a Long-Haul Trucks for Energy Management Applications

Super Truck II is a 48V mild hybrid class 8 truck with an all auxiliary loads powered purely by the battery pack. Electric Heating Ventilation and Air Conditioning (HVAC) load is the most prominent battery load during the hotel period, when the truck driver is resting inside the sleeper. For the PACCAR Super Truck II (ST-II) project a 48 V battery system provides the required power during the hotel period. A cabin-HVAC model estimates the electric load on the 48V battery system, allowing the control system to implement an efficient energy management strategy that avoids engine idling during the hotel period. The thermal model accounts for the sun load due to the time of day and the geographic location of the truck during the hotel period. The cabin-HVAC model has two parts. First, a grey box model with two heat exchangers (Condenser and Evaporator) working in unison with refrigerant mass flow rate as an input and HVAC load as an output. Second, a two-node cabin model formulated to estimate the cabin temperature as a function of the Global Horizontal Irradiance (GHI), HVAC load and ambient temperature. The models are calibrated using experimental cabin-HVAC system data as for long-haul class 8 truck (e.g. ST-II). Here, the model simulations show that the overall Root Mean Square Error (RMSE) value of 0.4°C between the experimental and simulated cabin temperature.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗
NASA NTRS1977

Life sciences Spacelab Mission Development test 3 (SMD 3) data management report

Development of a permanent data system for SMD tests was studied that would simulate all elements of the shuttle onboard, telemetry, and ground data systems that are involved with spacelab operations. The onboard data system (ODS) and the ground data system (GDS) were utilized. The air-to-ground link was simulated by a hardwired computer-to-computer interface. A patch board system was used on board to select experiment inputs, and the downlink configuration from the ODS was changed by a crew keyboard entry to support each experiment. The ODS provided a CRT display of experiment parameters to enable the crew to monitor experiment performance. An onboard analog system, with recording capability, was installed to handle high rate data and to provide a backup to the digital system. The GDS accomplished engineering unit conversion and limit sensing, and provided realtime parameter display on CRT's in the science monitoring area and the test control area.

Moseley, E. C.↗
NASA NTRS1975

General purpose simulation system of the data management system for space shuttle mission 18

The simulation program of the science and engineering data management system for the space shuttle is presented. The programming language used was General Purpose Simulation System V (OS). The data flow was modeled from its origin at the experiments or subsystems to transmission from the space shuttle. Mission 18 was the particular flight chosen for simulation. First, the general structure of the program is presented and the trade studies which were performed are identified. Inputs required to make runs are discussed followed by identification of the output statistics. Some areas for model modifications are pointed out. A detailed model configuration, program listing and results are included.

Bengtson, N. M.↗
DOE OSTI2013

Global Sensitivity Measures from Given Data

Simulation models support managers in the solution of complex problems. International agencies recommend uncertainty and global sensitivity methods as best practice in the audit, validation and application of scientific codes. However, numerical complexity, especially in the presence of a high number of factors, induces analysts to employ less informative but numerically cheaper methods. This work introduces a design for estimating global sensitivity indices from given data (including simulation input–output data), at the minimum computational cost. We address the problem starting with a statistic based on the L1-norm. A formal definition of the estimators is provided and corresponding consistency theorems are proved. The determination of confidence intervals through a bias-reducing bootstrap estimator is investigated. The strategy is applied in the identification of the key drivers of uncertainty for the complex computer code developed at the National Aeronautics and Space Administration (NASA) assessing the risk of lunar space missions. We also introduce a symmetry result that enables the estimation of global sensitivity measures to datasets produced outside a conventional input–output functional framework.

99 GENERAL AND MISCELLANEOUS↗
NASA NTRS2004

Improving Project Management with Simulation and Completion Distribution Functions

Despite the critical importance of project completion timeliness, management practices in place today remain inadequate for addressing the persistent problem of project completion tardiness. A major culprit in late projects is uncertainty, which most, if not all, projects are inherently subject to. This uncertainty resides in the estimates for activity durations, the occurrence of unplanned and unforeseen events, and the availability of critical resources. In response to this problem, this research developed a comprehensive simulation based methodology for conducting quantitative project completion time risk analysis. It is called the Project Assessment by Simulation Technique (PAST). This new tool enables project stakeholders to visualize uncertainty or risk, i.e. the likelihood of their project completing late and the magnitude of the lateness, by providing them with a completion time distribution function of their projects. Discrete event simulation is used within PAST to determine the completion distribution function for the project of interest. The simulation is populated with both deterministic and stochastic elements. The deterministic inputs include planned project activities, precedence requirements, and resource requirements. The stochastic inputs include activity duration growth distributions, probabilities for events that can impact the project, and other dynamic constraints that may be placed upon project activities and milestones. These stochastic inputs are based upon past data from similar projects. The time for an entity to complete the simulation network, subject to both the deterministic and stochastic factors, represents the time to complete the project. Repeating the simulation hundreds or thousands of times allows one to create the project completion distribution function. The Project Assessment by Simulation Technique was demonstrated to be effective for the on-going NASA project to assemble the International Space Station. Approximately $500 million per month is being spent on this project, which is scheduled to complete by 2010. NASA project stakeholders participated in determining and managing completion distribution functions produced from PAST. The first result was that project stakeholders improved project completion risk awareness. Secondly, using PAST, mitigation options were analyzed to improve project completion performance and reduce total project cost.

Cates, Grant R.↗
NASA NTRS2019

Usability Evaluation of Indicators of Energy-Related Problems in Commercial Airline Flight Decks

A series of pilot-in-the-loop flight simulation studies were conducted at NASA Langley Research Center to evaluate indicators aimed at supporting the flight crew’s awareness of problems related to energy states. Indicators were evaluated utilizing state-of-the-art flight deck systems such as on commercial air transport aircraft. This paper presents results for four technologies: (1) conventional primary flight display speed cues, (2) an enhanced airspeed control indicator, (3) a synthetic vision baseline that provides a flight path vector, speed error, and an acceleration cue, and (4) an aural airspeed alert that triggers when current airspeed deviates beyond a specified threshold from the selected airspeed. Full-mission high-fidelity flight simulation studies were conducted using commercial airline crews. Crews were paired by airline for common crew resource management procedures and protocols. Scenarios spanned a range of complex conditions while emulating several causal factors reported in recent accidents involving loss of energy state awareness by pilots. Data collection included questionnaires administered at the completion of flight scenarios, aircraft state data, audio/video recordings of flight crew, eye tracking, pilot control inputs, and researcher observations. Questionnaire response data included subjective measures of workload, situation awareness, complexity, usability, and acceptability. This paper reports relevant findings derived from subjective measures as well as quantitative measures.

Evans, Emory T.↗
DOE OSTI2026

Conditional distribution estimation of building characteristics with diffusion models for urban energy modeling

Understanding current energy consumption behavior in communities is critical for informing future energy use decisions and enabling efficient energy management. Urban energy models, which are used to simulate these energy use patterns, require large datasets with detailed building characteristics for accurate outcomes. However, such detailed characteristics at the individual building level are often unknown and costly to acquire, or unavailable. Through this work, we propose using a generative modeling approach to generate realistic building attributes to fill in the data gaps and finally provide complete characteristics as inputs to energy models. Our model learns complex, building-level patterns from training on a large-scale residential building stock model containing 2.2 million buildings. We employ a tabular diffusion-based framework that is designed to handle heterogeneous (discrete and continuous) features in tabular building data, such as occupancy, floor area, heating, cooling, and other equipment details. We develop a capability for conditional diffusion, enabling the imputation of missing building characteristics conditioned on known attributes. We conduct a comprehensive validation of our conditional diffusion model, firstly by comparing the generated conditional distributions against the underlying data distribution, and secondly, by performing a case study for a Baltimore residential region, showing the practical utility of our approach. Our work is one of the first to demonstrate the potential of generative modeling to accelerate building energy modeling workflows.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗
DOE OSTI2022

Modeling pre-Exascale AMR Parallel I/O Workloads via Proxy Applications

The present work investigates the modeling of preexascale input/output (I/O) workloads of Adaptive Mesh Refinement (AMR) simulations through a simple proxy application. We collect data from the AMReX Castro framework running on the Summit supercomputer for a wide range of scales and mesh partitions for the hydrodynamic Sedov case as a baseline to provide sufficient coverage to the formulated proxy model. The non-linear analysis data production rates are quantified as a function of a set of input parameters such as output frequency, grid size, number of levels, and the Courant-Friedrichs-Lewy (CFL) condition number for each rank, mesh level and simulation time step. Linear regression is then applied to formulate a simple analytical model which allows to translate AMReX inputs into MACSio proxy I/O application parameters, resulting in a simple “kernel” approximation for data production at each time step. Results show that MACSio can simulate actual AMReX nonlinear “static” I/O workloads to a certain degree of confidence on the Summit supercomputer using the present methodology. The goal is to provide an initial level of understanding of AMR I/O workloads via lightweight proxy applications models to facilitate autotune data management strategies in anticipation of exascale systems.

Godoy, William↗
DOE OSTI2019

ATLAS Data Carousel

The ATLAS experiment at CERN's LHC stores detector and simulation data in raw and derived data formats across more than 150 Grid sites world-wide, currently in total about 200PB on disk and 250PB on tape. Data have different access characteristics due to various computational workflows, and can be accessed from different media, such as remote I/O, disk cache on hard disk drives or SSDs. Also, larger data centers provide the majority of offline storage capability via tape systems. For the High-Luminosity LHC (HL-LHC), the estimated data storage requirements are several factors bigger than the present forecast of available resources, based on a flat budget assumption. On the computing side, ATLAS Distributed Computing was very successful in the last years with high performance and high throughput computing integration and in using opportunistic computing resources for the Monte Carlo simulation. On the other hand, equivalent opportunistic storage does not exist. ATLAS started the "Data Carousel" project to increase the usage of less expensive storage, i.e. tapes or even commercial storage, so it is not limited to tape technologies exclusively. Data Carousel orchestrates data processing between workload management, data management, and storage services with the bulk data resident on offline storage. The processing is executed by staging and promptly processing a sliding window of inputs onto faster buffer storage, such that only a small percentage of input data are available at any one time. With this project, we aim to demonstrate that this is the natural way to dramatically reduce our storage cost. The first phase of the project was started in the fall of 2018 and was related to I/O tests of the sites archiving systems. Phase II now requires a tight integration of the workload and data management systems. Additionally, the Data Carousel studies the feasibility to run multiple computing workflows from tape. The project is progressing very well and the results presented in this document will be used before the LHC Run 3.

97 MATHEMATICS AND COMPUTING↗
NASA NTRS2019

Fast-Time Simulation for Evaluating the Impact of Estimated Flight Ready Time Uncertainty on Surface Metering

NASA has been developing and demonstrating new concepts and technologies for Integrated Arrival, Departure, and Surface (IADS) traffic management capabilities under the Airspace Technology Demonstration 2 (ATD-2) project. One of the IADS capabilities in the ATD-2 project is surface metering enabled by a tactical surface scheduler to provide controllers with the pushback advisories for departures at gates. The tactical surface scheduler uses the estimated flight ready times provided by airlines, called Earliest Off-Block Times (EOBTs), as input to calculate the target off-block times for pushback advisories. However, the EOBTs are often inaccurate and deviate from the actual flight ready times, which may reduce the benefits of surface metering. In this paper, a linear regression model is developed to model the EOBT uncertainty distribution over time based on actual EOBT data collected at Charlotte airport. This EOBT model is integrated with a tactical surface scheduler and a fast-time simulation tool. To evaluate the impact of the EOBT accuracy on airport surface operations, fast-time simulations are implemented for selected traffic scenarios under different levels of modelled EOBT accuracy. The simulation results show that the EOBT uncertainty affects several performance metrics related to the surface metering, such as gate hold, taxi time reduction, and target takeoff time predictability, which in turn influences ATD-2's scheduler performance.

tactical surface scheduler↗