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At least 361 records · Page 20

Use of ultrasound in altitude decompression modeling

A model that predicts the probability of developing decompression sickness (DCS) with various denitrogenation schedules is being developed by the Armstrong Laboratory, using human data from previous exposures. It was noted that refinements are needed to improve the accuracy and scope of the model. A commercially developed ultrasonic echo imaging system is being used in this model development. Using this technique, bubbles images from a subject at altitude can be seen in the gall bladder, hepatic veins, vena cava, and chambers of the heart. As judged by their motion and appearance in the vena cava, venous bubbles near the heart range in size from 30 to 300 M. The larger bubbles skim along the top, whereas the smaller ones appear as faint images near the bottom of the vessel. Images from growing bubbles in a model altitude chamber indicate that they grow rapidly, going from 20 to 100 M in 3 sec near 30,000 ft altitude. Information such as this is valuable in verifying those aspects of the DCS model dealing with bubble size, their growth rate, and their site of origin.

Olson, Robert M.↗

NAS Demand Predictions, Transportation Systems Analysis Model (TSAM) Compared with Other Forecasts

The current work incorporates the Transportation Systems Analysis Model (TSAM) to predict the future demand for airline travel. TSAM is a multi-mode, national model that predicts the demand for all long distance travel at a county level based upon population and demographics. The model conducts a mode choice analysis to compute the demand for commercial airline travel based upon the traveler s purpose of the trip, value of time, cost and time of the trip,. The county demand for airline travel is then aggregated (or distributed) to the airport level, and the enplanement demand at commercial airports is modeled. With the growth in flight demand, and utilizing current airline flight schedules, the Fratar algorithm is used to develop future flight schedules in the NAS. The projected flights can then be flown through air transportation simulators to quantify the ability of the NAS to meet future demand. A major strength of the TSAM analysis is that scenario planning can be conducted to quantify capacity requirements at individual airports, based upon different future scenarios. Different demographic scenarios can be analyzed to model the demand sensitivity to them. Also, it is fairly well know, but not well modeled at the airport level, that the demand for travel is highly dependent on the cost of travel, or the fare yield of the airline industry. The FAA projects the fare yield (in constant year dollars) to keep decreasing into the future. The magnitude and/or direction of these projections can be suspect in light of the general lack of airline profits and the large rises in airline fuel cost. Also, changes in travel time and convenience have an influence on the demand for air travel, especially for business travel. Future planners cannot easily conduct sensitivity studies of future demand with the FAA TAF data, nor with the Boeing or Airbus projections. In TSAM many factors can be parameterized and various demand sensitivities can be predicted for future travel. These resulting demand scenarios can be incorporated into future flight schedules, therefore providing a quantifiable demand for flights in the NAS for a range of futures. In addition, new future airline business scenarios are investigated that illustrate when direct flights can replace connecting flights and larger aircraft can be substituted, only when justified by demand.

Viken, Jeff↗

Utilizing Traveler Demand Modeling to Predict Future Commercial Flight Schedules in the NAS

The current work incorporates the Transportation Systems Analysis Model (TSAM) to predict the future demand for airline travel. TSAM is a multi-mode, national model that predicts the demand for all long distance travel at a county level based upon population and demographics. The model conducts a mode choice analysis to compute the demand for commercial airline travel based upon the traveler s purpose of the trip, value of time, cost and time of the trip,. The county demand for airline travel is then aggregated (or distributed) to the airport level, and the enplanement demand at commercial airports is modeled. With the growth in flight demand, and utilizing current airline flight schedules, the Fratar algorithm is used to develop future flight schedules in the NAS. The projected flights can then be flown through air transportation simulators to quantify the ability of the NAS to meet future demand. A major strength of the TSAM analysis is that scenario planning can be conducted to quantify capacity requirements at individual airports, based upon different future scenarios. Different demographic scenarios can be analyzed to model the demand sensitivity to them. Also, it is fairly well know, but not well modeled at the airport level, that the demand for travel is highly dependent on the cost of travel, or the fare yield of the airline industry. The FAA projects the fare yield (in constant year dollars) to keep decreasing into the future. The magnitude and/or direction of these projections can be suspect in light of the general lack of airline profits and the large rises in airline fuel cost. Also, changes in travel time and convenience have an influence on the demand for air travel, especially for business travel. Future planners cannot easily conduct sensitivity studies of future demand with the FAA TAF data, nor with the Boeing or Airbus projections. In TSAM many factors can be parameterized and various demand sensitivities can be predicted for future travel. These resulting demand scenarios can be incorporated into future flight schedules, therefore providing a quantifiable demand for flights in the NAS for a range of futures. In addition, new future airline business scenarios are investigated that illustrate when direct flights can replace connecting flights and larger aircraft can be substituted, only when justified by demand.

Viken, Jeff↗

Dynamic Scheduling: Target of Opportunity Observations of Gravitational Wave Events

The simultaneous detection of electromagnetic and gravitational waves from the coalescence of two neutron stars (GW170817 and GRB170817A) has ushered in a new era of ‘multimessenger’ astronomy, with electromagnetic detections spanning from gamma to radio. This great opportunity for new scientific investigations raises the issue of how the available multimessenger tools can best be integrated to constitute a powerful method to study the transient Universe in particular. To facilitate the classification of possible optical counterparts to gravitational wave events, it is important to optimize the scheduling of observations and the filtering of transients, both key elements of the follow-up process. In this work, we describe the existing workflow whereby telescope networks such as GRANDMA and GROWTH are currently scheduled; we then present modifications we have developed for the scheduling process specifically, so as to face the relevant challenges that have appeared during the latest observing run of Advanced LIGO and Advanced Virgo. We address issues with scheduling more than one epoch for multiple fields within a skymap, especially for large and disjointed localizations. This is done in two ways: by optimizing the maximum number of fields that can be scheduled and by splitting up the lobes within the skymap by right ascension to be scheduled individually. In addition, we implement the ability to take previously observed fields into consideration when rescheduling. We show the improvements that these modifications produce in making the search for optical counterparts more efficient, and we point to areas needing further improvement.

Gravitational waves↗

Conflict-Aware Scheduling Algorithm

conflict-aware scheduling algorithm is being developed to help automate the allocation of NASA s Deep Space Network (DSN) antennas and equipment that are used to communicate with interplanetary scientific spacecraft. The current approach for scheduling DSN ground resources seeks to provide an equitable distribution of tracking services among the multiple scientific missions and is very labor intensive. Due to the large (and increasing) number of mission requests for DSN services, combined with technical and geometric constraints, the DSN is highly oversubscribed. To help automate the process, and reduce the DSN and spaceflight project labor effort required for initiating, maintaining, and negotiating schedules, a new scheduling algorithm is being developed. The scheduling algorithm generates a "conflict-aware" schedule, where all requests are scheduled based on a dynamic priority scheme. The conflict-aware scheduling algorithm allocates all requests for DSN tracking services while identifying and maintaining the conflicts to facilitate collaboration and negotiation between spaceflight missions. These contrast with traditional "conflict-free" scheduling algorithms that assign tracks that are not in conflict and mark the remainder as unscheduled. In the case where full schedule automation is desired (based on mission/event priorities, fairness, allocation rules, geometric constraints, and ground system capabilities/ constraints), a conflict-free schedule can easily be created from the conflict-aware schedule by removing lower priority items that are in conflict.

Wang, Yeou-Fang↗

DOE Award No.: DE-FE0023919 Phase 4 Scientific/Technical Report

This is the Phase 4 Report for the ‘Deepwater Methane Hydrate Characterization and Scientific Assessment or Genesis of Methane Hydrates in the Gulf of Mexico (GOM2)’ research project (DOE Award No. DE-FE0023919). The report summarizes activities from October 1, 2019 to September 30, 2020. The project is led by the University of Texas at Austin (UT). The project objective is to gain insight into the nature, formation, occurrence and physical properties of methane hydrate-bearing sediments for the purpose of methane hydrate resource appraisal through the planning and execution of drilling, coring, logging, testing and analytical activities that assess the geologic occurrence, regional context, and characteristics of marine methane hydrate deposits in the Gulf of Mexico outer continental shelf (OCS). We published a dedicated American Association of Petroleum Geologists Bulletin volume describing initial results from the UT-GOM2-1 expedition in Sept. 2020. This is part 1 of a multi-volume commitment by AAPG to this project. We further confirmed that the natural gas in hydrate at GC-955 was formed by primary microbial processes (>76.1 %). The in-situ effective permeability hydrate-bearing sandy silts at the GC-955 reservoir ranges from 0.1 md (1.0×10-16 m2) to 2.4 md (2.4×10-15m2) in cores with 83% to 93% hydrate saturation. The intrinsic permeability (the single phase permeability) is estimated from reconstituted samples to be ~12 md (1.2×10-14 m2) to ~41 md (4.1×10-14 m2). We used observation and models to interpret that the core degradation that is found in pressure cores is due to dissociation of the methane hydrate in the outer circumference of the core and dissolution of that methane into the fresh pore water that the core is stored with. We are designing approaches to minimize this core loss in the future. We spent an enormous amount of effort to further improve the ability of the pressure coring tool (the PCTB) to pressure seal correctly. We completed upgrading the upper section of the PCTB to address poor pressure. We successful tested the modifications at Geotek’s test facility in Salt Lake City (Bench Test II). We completed a Land Test of the PCTB at the Schlumberger Cameron Test and Training Facility (CTTF). The tool did not seal in 6 out of 7 tests and we clearly demonstrated that cuttings were wedging in the ball valve assembly, keeping the ball valve from sealing. We reproduced the failure mechanism observed during the land test at Salt Lake City and confirmed the sensitivity of the ball valve assembly to grit. Geotek designed and tested 9 modifications to address this issue and the PCTB is now 100% successfully sealing in the presence of grit. Our science expedition is scheduled for spring 2022 and we are fully focused on preparing for this. UT and Ohio State completed a Shallow Hazard Assessment report for each proposed UT-GOM2-2 drilling location, pursuant to 30 CFR 250.214(f) and 250.244 (f). The Shallow Hazard Reports will accompany the UT-GOM2-2 Exploration Plan that is submitted to BOEM, and completes the geological and geophysical analysis for UT-GOM2-2 permitting efforts. We updated the UT-GOM2-2 Operations Plan (Version 1). We completed the UT-GOM2-2 Science and Sample Distribution Plan (Version 1). We evaluated the scope, budget, and schedule that would result from using a commercial vessel. We developed detailed drilling schedule, mud volume, and resource estimates. We developed a vessel specification document and a well plan, and sent these documents to prospective vessel contractors.

03 NATURAL GAS↗

Space Chicken: A Historical Look at How the Critical Path Changes over a Mission’s Development

The critical path in schedule analysis defines the series of tasks that have no schedule slack leading to the delivery of a system. The critical path for NASA science missions, which typically runs through a spacecraft subsystem or a scientific instrument, is dynamic and changes over the development lifetime of a project. Often the critical path at the start of preliminary design will be through a specific spacecraft subsystem while the final, delivered critical path item is often a scientific instrument that is delivered late. The research for this paper looks at the postulated critical path at different milestones, and the actual critical path item at final delivery, for a variety of NASA science missions to understand what elements are impacting the delivery schedule the most. Recommendations are made based on these quantitative results relative to what elements should potentially be considered more often in early development schedules to more robustly plan for development issues.

Bitten, Robert↗

Space network scheduling benchmark: A proof-of-concept process for technology transfer

This paper describes a detailed proof-of-concept activity to evaluate flexible scheduling technology as implemented in the Request Oriented Scheduling Engine (ROSE) and applied to Space Network (SN) scheduling. The criteria developed for an operational evaluation of a reusable scheduling system is addressed including a methodology to prove that the proposed system performs at least as well as the current system in function and performance. The improvement of the new technology must be demonstrated and evaluated against the cost of making changes. Finally, there is a need to show significant improvement in SN operational procedures. Successful completion of a proof-of-concept would eventually lead to an operational concept and implementation transition plan, which is outside the scope of this paper. However, a high-fidelity benchmark using actual SN scheduling requests has been designed to test the ROSE scheduling tool. The benchmark evaluation methodology, scheduling data, and preliminary results are described.

Moe, Karen↗

Achieving reutilization of scheduling software through abstraction and generalization

Reutilization of software is a difficult goal to achieve particularly in complex environments that require advanced software systems. The Request-Oriented Scheduling Engine (ROSE) was developed to create a reusable scheduling system for the diverse scheduling needs of the National Aeronautics and Space Administration (NASA). ROSE is a data-driven scheduler that accepts inputs such as user activities, available resources, timing contraints, and user-defined events, and then produces a conflict-free schedule. To support reutilization, ROSE is designed to be flexible, extensible, and portable. With these design features, applying ROSE to a new scheduling application does not require changing the core scheduling engine, even if the new application requires significantly larger or smaller data sets, customized scheduling algorithms, or software portability. This paper includes a ROSE scheduling system description emphasizing its general-purpose features, reutilization techniques, and tasks for which ROSE reuse provided a low-risk solution with significant cost savings and reduced software development time.

Wilkinson, George J.↗

Robust telescope scheduling

This paper presents a technique for building robust telescope schedules that tend not to break. The technique is called Just-In-Case (JIC) scheduling and it implements the common sense idea of being prepared for likely errors, just in case they should occur. The JIC algorithm analyzes a given schedule, determines where it is likely to break, reinvokes a scheduler to generate a contingent schedule for each highly probable break case, and produces a 'multiply contingent' schedule. The technique was developed for an automatic telescope scheduling problem, and the paper presents empirical results showing that Just-In-Case scheduling performs extremely well for this problem.

Swanson, Keith↗

Managing Action Duration Uncertainty with Just-In-Case Scheduling

Some applications involve automatic generation and execution of schedules that contain actions with uncertain durations. Such uncertainty can cause schedules to break during execution. This paper presents a technique, called Just-In-Case scheduling or JIC, for building robust schedules that tend not to break. The technique implements the common sense idea of being prepared for likely errors, just in case they should occur. The JIC algorithm analyzes a given schedule, determines where it is likely to break, reinvokes the scheduler to generate a contingent schedule for each highly probable break case, and produces a "multiply contingent" schedule. The technique was developed for a real telescope scheduling problem, and the paper presents empirical results showing that Just-In-Case scheduling performs extremely well for this problem.

Bresina, John↗

Resource representation in COMPASS

A set of viewgraphs on resource representation in COMPASS is given. COMPASS is an incremental, interactive, non-chronological scheduler written in Ada with an X-windows user interface. Beginning with an empty schedule, activities are added to the schedule one at a time, taking into consideration the placement of the activities already on the timeline and the resources that have been reserved for them. The order that the activities are added to the timeline and their location on the timeline are controlled by selection and placement commands invoked by the user. The order that activities are added to the timeline and their location are independent. The COMPASS code library is a cost effective platform for the development of new scheduling applications. It can be effectively used off the shelf for compatible scheduling applications or it can be used as a parts library for the development of custom scheduling systems.

Fox, Barry R.↗

A Genetic Algorithm Tool (splicer) for Complex Scheduling Problems and the Space Station Freedom Resupply Problem

The Space Station Freedom will require the supply of items in a regular fashion. A schedule for the delivery of these items is not easy to design due to the large span of time involved and the possibility of cancellations and changes in shuttle flights. This paper presents the basic concepts of a genetic algorithm model, and also presents the results of an effort to apply genetic algorithms to the design of propellant resupply schedules. As part of this effort, a simple simulator and an encoding by which a genetic algorithm can find near optimal schedules have been developed. Additionally, this paper proposes ways in which robust schedules, i.e., schedules that can tolerate small changes, can be found using genetic algorithms.

Wang, Lui↗

Onboard Automated Scheduling for the Mars 2020 Rover

The Mars 2020 Mission, scheduled to land on Mars February 18, 2021, has developed an onboard scheduling system [1]. The rationale for the onboard scheduler is to enable the Perseverance rover to adjust its activities in response to activities taking longer or shorter than planned, or using more or less resources than expected, as effectively using these resources could significantly improve rover productivity [2]. If deployed, the onboard scheduler would be an unprecedented use of Artificial Intelligence/Autonomy onboard software in a key role for a major mission.

Biehl, J.↗

Assessment of Delivery Accuracy in an Operational-Like Environment

In order to enable arrival management concepts and solutions in a Next Generation Air Transportation System (NextGen) environment, ground-based sequencing and scheduling functions were developed to support metering operations in the National Airspace System. These sequencing and scheduling tools are designed to assist air traffic controllers in developing an overall arrival strategy, from enroute down to the terminal area boundary. NASA developed a ground system concept and protoype capability called Terminal Sequencing and Spacing (TSAS) to extend metering operations into the terminal area to the runway. To demonstrate the use of these scheduling and spacing tools in an operational-like environment, the FAA, NASA, and MITRE conducted an Operational Integration Assessment (OIA) of a prototype TSAS system at the FAA's William J. Hughes Technical Center (WJHTC). This paper presents an analysis of the arrival management strategies utilized and delivery accuracy achieved during the OIA. The analysis demonstrates how en route preconditioning, in various forms, and schedule disruptions impact delivery accuracy. As the simulation spanned both enroute and terminal airspace, the use of Ground Interval Management - Spacing (GIM-S) enroute speed advisories was investigated. Delivery accuracy was measured as the difference between the Scheduled Time of Arrival (STA) and the Actual Time of Arrival (ATA). The delivery accuracy was computed across all runs conducted during the OIA, which included deviations from nominal operations which are known to commonly occur in real operations, such as schedule changes and missed approaches. Overall, 83% of all flights were delivered into the terminal airspace within +/- 30 seconds of their STA and 94% of flights were delivered within +/- 60 seconds. The meter fix delivery accuracy standard deviation was found to be between 36 and 55 seconds across all arrival procedures. The data also showed when schedule disruptions were excluded, the percentage of aircraft delivered within +/- 30 seconds was between 85 and 90% across the various arrival procedures at the meter fix. This paper illustrates the ability to meet new delivery accuracy requirements in an operational-like environment using operational systems and NATCA controller participants, while also including common events that might cause disruptions to the schedule and overall system.

Air Traffic Scheduling↗

Crew Autonomy Scheduling: Scheduling Performance Pilot Study

The purpose of this pilot study is to quantify crew performance in self-scheduling through Playbook, a mobile-based scheduling and planning tool. By investigating human performance within the task of self-scheduling, we can further develop countermeasures that can mitigate deficient scheduling performance, and evaluate changes as a result of these countermeasures. Moreover, this research can advise the development of standards and guidelines for autonomous crews in future missions. In human spaceflight today, the task of planning crew member’s schedules falls to Ops Planners. It takes many weeks to plan due to the complex impact each day-to-day activity can have on other activities, crew members, and resources. These impacts are measured as constraints, and these constraints can result in temporal, ordering, or resource requirements. As future spaceflight missions span longer distances and the latency of communication between the crew and Mission Control Center (MCC) increases, the need for crew members to work independently from MCC will also increase. This results in a need for crew members to be able to autonomously plan and adjust their own schedules.

planning↗

A scheduling algorithm for Spacelab telescope observations

An algorithm is developed for sequencing and scheduling of observations of stellar targets by equipment on Spacelab. The method is a general one. The scheduling problem is defined and examined. The method developed for its solution is documented. Suggestions for further development and implementation of this method are made.

Grone, B.↗

What we were asked to do

Recommendations are made after 32 interviews, lesson identification, lesson analysis, and mission characteristics identification. The major recommendations are as follows: (1) to develop end-to-end planning and scheduling operations concepts by mission class and to ensure their consideration in system life cycle documentation; (2) to create an organizational infrastructure at the Code 500 level, supported by a Directorate level steering committee with project representation, responsible for systems engineering of end-to-end planning and scheduling systems; (3) to develop and refine mission capabilities to assess impacts of early mission design decisions on planning and scheduling; and (4) to emphasize operational flexibility in the development of the Advanced Space Network, other institutional resources, external (e.g., project) capabilities and resources, operational software and support tools.

Source record↗