SEARCH · Search NASA

Results for “Parallel connection”

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.

SourceResearch connectionFrom yearThrough year

Quote a phrase for an exact phrase match. Source license links do not imply unrestricted reuse.

643 records · Page 36

All sources NASA NTRS DOE OSTI

NASA NTRS2011

Software Architecture to Support the Evolution of the ISRU RESOLVE Engineering Breadboard Unit 2 (EBU2)

The In-Situ Resource Utilization (ISRU) Regolith & Environmental Science and Oxygen & Lunar Volatiles Extraction (RESOLVE) software provides operation of the physical plant from a remote location with a high-level interface that can access and control the data from external software applications of other subsystems. This software allows autonomous control over the entire system with manual computer control of individual system/process components. It gives non-programmer operators the capability to easily modify the high-level autonomous sequencing while the software is in operation, as well as the ability to modify the low-level, file-based sequences prior to the system operation. Local automated control in a distributed system is also enabled where component control is maintained during the loss of network connectivity with the remote workstation. This innovation also minimizes network traffic. The software architecture commands and controls the latest generation of RESOLVE processes used to obtain, process, and quantify lunar regolith. The system is grouped into six sub-processes: Drill, Crush, Reactor, Lunar Water Resource Demonstration (LWRD), Regolith Volatiles Characterization (RVC) (see example), and Regolith Oxygen Extraction (ROE). Some processes are independent, some are dependent on other processes, and some are independent but run concurrently with other processes. The first goal is to analyze the volatiles emanating from lunar regolith, such as water, carbon monoxide, carbon dioxide, ammonia, hydrogen, and others. This is done by heating the soil and analyzing and capturing the volatilized product. The second goal is to produce water by reducing the soil at high temperatures with hydrogen. This is done by raising the reactor temperature in the range of 800 to 900 C, causing the reaction to progress by adding hydrogen, and then capturing the water product in a desiccant bed. The software needs to run the entire unit and all sub-processes; however, throughout testing, many variables and parameters need to be changed as more is learned about the system operation. The Master Events Controller (MEC) is run on a standard laptop PC using Windows XP. This PC runs in parallel to another laptop that monitors the GC, and a third PC that monitors the drilling/ crushing operation. These three PCs interface to the process through a CompactRIO, OPC Servers, and modems.

Moss, Thomas↗

NASA NTRS2006

Space Activism as an Epiphanic Belief System

Years of interaction with young people in the space industry and in space activists groups led to my observation that many such individuals can cite a quite specific life event that triggered a life-long interest in or commitment to creating a space future. I am particularly intrigued by parallels between such experiences and the phenomenon of epiphanic experiences among committed Christians. I see analogies between the puzzlement among space activists and among Christian groups as to the reasons for so many people being "unbelievers." At a small international meeting on lunar exploration in 2003, I heard two separate lunch speakers cite such personal experiences. At the beginning of a break in that meeting, I grabbed the microphone from the chairman and asked each person to write down on a pad by his chair whether or not he (or she) had experienced a specific event that led to their involvement in space. If the answer was positive, I asked for a brief narrative, for their age at the time, and for their current age. I received 53 submissions, 20% of which simply stated that their involvement in space exploration was happenstance. (Apollo astronaut John Young was among these.) The other 80% of the submissions had specific stories. The ages at the time of the epiphany ranged from 4 to 47; and their current ages ranged from 22 to 78. I will present a high-level characterization of these inputs. Interest in space exploration as a form of belief system is consistent with choosing NASA goals for the purpose of inspiration and with phenomena such as the "Overview Effect". More research might explore what form the transcendent experience takes and whether it might be associated with feelings of universal connection such as the noosphere or "The Force". From a pragmatic point of view, outreach strategies for exploration should focus on giving individuals access to personal, potentially transformational experiences as opposed to astronaut talks at civic clubs.

Mendell, Wendell↗

NASA NTRSDate not supplied

NASA Aeronautics Sustainable Aviation Overview

We live in challenging but exciting times for aviation as the sector continues to emerge from the unprecedented impact of a global pandemic while addressing its contribution to global warming. This perfect storm provides opportunity and the drivers that can lead to the most substantial changes the aviation sector has seen since the convergence of jet engines and swept wings over 60 years ago. The reality is we are entering the dawn of a new era of sustainable aviation full of opportunities and challenges that must economically address the health and transportation needs of society with unprecedentedly low impact on local, regional, and global environments. Today, commercial aviation physically connects countries across the globe and is an integral, critical part of today’s expanding global economy. Commercial aviation relies almost entirely on subsonic transport aircraft to constantly move people and goods from one place to another across the globe. While an effective means of transportation providing an unmatched combination of payload, speed, and range, future subsonic aircraft must continue to improve to meet efficiency, environmental, and economic goals established around the world to sustain the substantial growth projected in this well-established market. Commercial supersonic transports have come and gone in the global market, but they are on the verge of reemerging. Vertical lift vehicles leveraging breakthroughs in autonomous systems and electrified propulsion are positioned for massive growth in local and regional markets leading to daily flights within metropolitan areas that may exceed that across countries. To succeed, these new aircraft must be sustainable from day 1. NASA Aeronautics has a long history of contributions to aviation, and today it continues to address the challenge of sustainable growth of the traditional air transportation system through the research and development of systems and technologies for future aircraft and airspace operations. Research programs over the last decade have set the stage to demonstrate key technologies offering step-change performance and environmental impact. Through a Sustainable Flight National Partnership, NASA will partner with industry, academia, and other government agencies to demonstrate the most promising technologies during the 2020s to enable revolutionary systems in the early 2030s. In parallel, NASA will explore systems and technologies for further benefits approaching zero environmental impact beyond the 2030s. Similarly, NASA programs are addressing the challenges of emerging markets enabled by vertical take-off/landing and low-boom supersonic cruise. This oral-only presentation will focus on opportunities and challenges in the traditional subsonic transport while touching on emerging vertical lift and supersonic commercial aviation markets. NASA’s recent contributions, ongoing research, and plans for sustainable aviation will be discussed, including airframe, propulsion, and integrated vehicle systems and technologies.

James A. Kenyon↗

NASA NTRS1992

Machine Learning Techniques in Optimal Design

Many important applications can be formalized as constrained optimization tasks. For example, we are studying the engineering domain of two-dimensional (2-D) structural design. In this task, the goal is to design a structure of minimum weight that bears a set of loads. A solution to a design problem in which there is a single load (L) and two stationary support points (S1 and S2) consists of four members, E1, E2, E3, and E4 that connect the load to the support points is discussed. In principle, optimal solutions to problems of this kind can be found by numerical optimization techniques. However, in practice [Vanderplaats, 1984] these methods are slow and they can produce different local solutions whose quality (ratio to the global optimum) varies with the choice of starting points. Hence, their applicability to real-world problems is severely restricted. To overcome these limitations, we propose to augment numerical optimization by first performing a symbolic compilation stage to produce: (a) objective functions that are faster to evaluate and that depend less on the choice of the starting point and (b) selection rules that associate problem instances to a set of recommended solutions. These goals are accomplished by successive specializations of the problem class and of the associated objective functions. In the end, this process reduces the problem to a collection of independent functions that are fast to evaluate, that can be differentiated symbolically, and that represent smaller regions of the overall search space. However, the specialization process can produce a large number of sub-problems. This is overcome by deriving inductively selection rules which associate problems to small sets of specialized independent sub-problems. Each set of candidate solutions is chosen to minimize a cost function which expresses the tradeoff between the quality of the solution that can be obtained from the sub-problem and the time it takes to produce it. The overall solution to the problem, is then obtained by solving in parallel each of the sub-problems in the set and computing the one with the minimum cost. In addition to speeding up the optimization process, our use of learning methods also relieves the expert from the burden of identifying rules that exactly pinpoint optimal candidate sub-problems. In real engineering tasks it is usually too costly to the engineers to derive such rules. Therefore, this paper also contributes to a further step towards the solution of the knowledge acquisition bottleneck [Feigenbaum, 1977] which has somewhat impaired the construction of rulebased expert systems.

Cerbone, Giuseppe↗

NASA NTRS2018

Evaluation of Crew-Centric Onboard Mission Operations Planning and Execution Tool: Year 2

Currently, mission planning for the International Space Station (ISS) is largely affected by ground operators in mission control. The task of creating a week-long mission plan for ISS crew takes dozens of people multiple days to complete, and is often created far in advance of its execution. As such, re-planning or adapting to changing real-time constraints or emergent issues is similarly taxing. As we design for future mission operations concepts to other planets or areas with limited connectivity to Earth, more of these ground-based tasks will need to be handled autonomously by the crew onboard.There is a need for a highly usable (including low training time) tool that enables efficient self-scheduling and execution within a single package. The ISS Program has identified Playbook as a potential option. It already has high crew acceptance as a plan viewer from previous analogs and can now support a crew self-scheduling assessment on ISS or on another mission. The goals of this work, a collaboration between the Human Research Program and the ISS Program, are to inform the design of systems for more autonomous crew operations and provide a platform for research on crew autonomy for future deep space missions. Our second year of the research effort have included new insights on the crew self-scheduling sessions performed by the crew through use on the HERA (Human Exploration Research Analog) and NEEMO (NASA Extreme Environment Mission Operations) analogs. Use on the NEEMO analog involved two self-scheduling strategies where the crew planned and executed two days of EVAs (Extra-Vehicular Activities). On HERA year two represented the first HERA campaign where we were able to perform research tasks. This involved selected flexible activities that the crew could schedule, mock timelines where the crew completed more complex planning exercises, usability evaluation of the crew self-scheduling features, and more insights into the limit of plan complexity that the crew could effectively self-schedule. In parallel we have added in new features and functionality in the Playbook tool based off of our insights from crew self-scheduling in the NASA analogs. In particular this year we have added in the ability for the crew to add, edit, and remove their own activities in the Playbook tool, expanding the type of planning and re-planning possible in the tool and opening up the ability for more free form plan creation. The ability to group and manipulate groups of activities from the plan task list was also added, allowing crew members to add predefined sets of activities onto their mission timeline. In addition we also added a way for crew members to roll back changes in their plan, in order to allow an undo like capability. These features expand and complement the initial self-scheduling features added in year one with the goal of making crew autonomous planning more efficient. As part of this work we have also finished developing the first version of our Playbook Data Analysis Tool, a research tool built to interpret and analyze the unobtrusively collected data obtained during the NASA analog missions through Playbook. This data which includes user click interaction as well as plan change information, through the Playbook Data Analysis Tool, allows us to playback this information as if a video camera was mounted over the crewmember's tablet. While the primary purpose of this tool is to allow usability analysis of crew self-scheduling sessions used on the NASA analog, since the data collected is structured, the tool can automatically derive metrics that would be traditionally tedious to achieve without manual analysis of video playback. We will demonstrate and discuss the ability for future derived metrics to be added to the tool. In addition to the current data and results gathered in year two we will also discuss the preparation and goals of our International Space Station (ISS) onboard technology demonstration with Playbook. This technology demonstration will be preformed as part of the CAST payload starting in late 2016.

onboard planning↗

NASA NTRS2008

Ultra-Stable Beacon Source for Laboratory Testing of Optical Tracking

The ultra-stable beacon source (USBS) provides a laser-beam output with a very low angular jitter and can be used as an absolute angular reference to simulate a beacon in the laboratory. The laser is mounted on the top of a very short (approximately equal to 1 m) inverted pendulum (IP) with its optical axis parallel to the carbon fiber pendulum leg. The 85-cm, carbon fiber rods making up the leg are very lightweight and rigid, and are supported by a flex-joint at the bottom (see figure). The gimbal-mounted laser is a weight-adjustable load of about 1.5 kg with its center of rotation co-located with the center of percussion of the inverted pendulum. This reduces the coupling of transverse motion at the base of the pendulum to angular motion of the laser at the top. The inverted pendulum is mounted on a gimbal with its center of rotation coinciding with the pivot position of the inverted pendulum flexure joint. This reduces coupling of ground tilt at the inverted pendulum base to motion of the laser mounted at the top. The mass of the top gimbal is adjusted to give the pendulum a very low resonant frequency (approximately equal to 10 mHz) that filters transverse seismic disturbances from the ground where the base is attached. The motion of the IP is monitored by an optical-lever sensor. The laser light is reflected by the mirror on the IP, and then is detected by a quadrant photo-detector (QPD). The position of the beam spot on the QPD corresponds to the tilt of the IP. Damping of this motion is provided by two coil and magnet pairs. The bottom gimbal mount consists of two plates. The IP is mounted on the second plate. The first plate is supported by two posts through needles and can be rotated about the axis connecting the tips of the needles. The second plate hangs from the first plate and can be rotated about the axis perpendicular to the first plate. As a result, the second plate acts as a two-axis rotation stage. Its center of rotation is located at the effective bending point of the flex-joint. The second plate is pressed against two screw actuators by the weight of the IP. The screw actuators are orthogonal to each other and are used to adjust the inclination of the second plate. The actuators are driven by stepper motors. The whole IP system is housed in a box made of Lexan plastic plates to provide isolation from air currents and temperature variations. The signals from the sensors are processed and recorded with a PC using the xPC Target realtime environment of Math- Works. The control algorithms are written using the Simulink package from The MathWorks.

Aso, Yoichi↗

NASA NTRS2015

A Data Exploration Tool for Large Sets of Spectra

We present an exploration tool for very large spectrum data sets such as the SDSS (Sloan Digital Sky Survey), LAMOST (Large Sky Area Multi-Object Fiber Spectroscopic Telescope), and 4MOST (4-meter Multi-Object Spectroscopic Telescope) data sets. The tool works in two stages: the first uses batch processing and the second runs interactively. The latter employs the NASA hyperwall, a configuration of 128 workstation displays (8 by 16 array) controlled by a parallelized software suite running on NASA's Pleiades supercomputer. The stellar subset of the Sloan Digital Sky Survey, DR10, was chosen to show how the our tool may be used. In stage one, SDSS files for 569,740 stars are processed through our data pipeline. The pipeline fits each spectrum using an iterative continuum algorithm, distinguishing emission from absorption and handling molecular absorption bands correctly. It then measures 1659 discrete atomic and molecular spectral features that were carefully preselected based on their likelihood of being visible at some spectral type. The depths relative to the local continuum at each feature wavelength are determined for each spectrum: these depths, the local S/N (signal to noise ratio) level, and DR10-supplied variables such as magnitudes, colors, positions, and radial velocities are the basic measured quantities used on the hyperwall. In stage two, each hyperwall panel is used to display a 2-D scatter plot showing the depth of feature A vs the depth of feature B for all of the stars. A and B change from panel to panel. The relationships between the various (A,B) strengths and any distinctive clustering are immediately apparent when examining and inter-comparing the different panels on the hyperwall. The interactive software allows the user to select the stars in any interesting region of any 2-D plot on the hyperwall, immediately rendering the same stars on all the other 2-D plots in a unique color. The process may be repeated multiple times, each selection displaying a distinctive color on all the plots. At any time, the spectra of the selected stars may be examined in detail on a connected workstation display. We illustrate how our approach allows us to quickly isolate and examine such interesting stellar subsets as EMP (Extremely Metal‐Poor) stars, CV (Cataclymic Variable) stars and C (Carbon)-rich stars.

Data Exploration↗

NASA NTRS2023

High-Rate Delay Tolerant Networking (HDTN) User Guide Version 1.0

Delay Tolerant Networking (DTN) has been identified as a key technology to enable and facilitate the development and growth of future space networks. Classically, space communications networks are collections of disparate links that are manually managed either point-to-point or use space relays. The accelerating accessibility of space enables a new scaling of space nodes, yet both the manual management of configurations and scheduling and the lack of structure connecting links precisely prohibit scaling. This challenge gives rise to newer and larger classes of communications needs that are met by DTN, which must overcome the disconnection, disruption, latency, and mobility featured in space communications systems. DTN joins the underlying links as an overlay, and can be made to communicate over any protocol stack. The core actions of DTN are store, carry, and forward, where data are stored instead of dropped if there is no immediately available outduct. It does this by taking the DTN unit of data, bundles, and providing necessary layers to adapt these bundles to the underlying transport protocols of choice; these are called convergence layers. DTN's Bundle Protocol (BP) can then be used on top of terrestrial protocol stacks, such as TCP/IP, as well as protocols for space, such as LTP/AOS, all in the same network. For emphasis it is noted that bundles can be of essentially any size, and hence this convergence to lower layers of choice is necessary. Existing DTN implementations have operated in constrained environments with limited resources, resulting in low data speeds. However, as various technologies have advanced, data transfer rates and efficiency have advanced, which has pushed the need for a DTN implementation for ground systems and for spacecraft that is performance-oriented in order to not impose an unnecessary bottleneck. High-rate Delay Tolerant Networking (HDTN) takes advantage of modern hardware platforms to substantially reduce latency and improve throughput compared to today’s DTN operations. The HDTN implementation maintains interoperability with existing deployments of DTN that conform to IETF RFCs 4838, 5050, and 9171. At the same time, HDTN defines a new data format better suited to higher-rate operation. It defines and adopts a massively parallel pipelined and message-oriented architecture, allowing the system to scale gracefully as its resources increase. HDTN’s architecture also supports hooks to replace various processing pipeline elements with specialized hardware accelerators. This offers improved Size, Weight, and Power (SWaP) characteristics while reducing development complexity and cost.

Delay Tolerant Networking↗

NASA NTRS2024

High-Rate Delay Tolerant Networking (HDTN) User Guide Version 1.3.0

Delay Tolerant Networking↗

NASA NTRSDate not supplied

A Machine Learning Approach to Improve Air Traffic Management Initiatives

Collaborating closely with commercial air carriers and related organizations, the Federal Aviation Administration(FAA) regulates air traffic and ensures the safety and efficiency of air operations. Air traffic controllers make strategic decisions, such as delaying, rerouting, or canceling flights, partly based on guidance provided by the FAA’s Air TrafficControl System Command Center (ATCSCC). The guidance includes, among other things, control measures known asTraffic Management Initiatives (TMIs) designed to enhance safety and improve operational efficiency. TMIs play a crucial role in managing the demand and capacity within the U.S. National Airspace System (NAS). Two major TMIs that are routinely used (primarily to mitigate the adverse effects of bad weather) are Ground Delay Programs (GDPs) andGround Stops (GSs). In a GDP, flights destined for airports facing thunderstorm activity experience delays at their origin airports. This proactive approach minimizes the risk of routing aircraft through hazardous weather conditions and also replaces (fuel burning) airborne delays with ground delays. In a GS, a temporary restriction is imposed on the departure or arrival of aircraft at a specific airport or within a designated airspace. Although other TMIs (e.g., miles-in-trail) are also implemented as part of (air) traffic flow management in the NAS, the focus of this work is on GDPs and GSs. Since TMIs, by design, lead to flight delays or cancellations, it is crucial to put in place the right set of parameters(e.g., scope and duration of the GDP). For example, when the end time of a GDP extends beyond what is necessary, it imposes unnecessary delays on departing flights. This situation could occur as a result of inaccurate prediction of the(required) duration of the GDP based on the weather forecast. On the other hand, if a GDP ends prematurely before the underlying capacity constraints are resolved at the destination airport, it may result in airborne holding. The delicate balance lies in matching the termination of the GDP precisely with the resolution of capacity constraints, avoiding both the imposition of unnecessary ground delays and the need for airborne holding due to premature program termination.Failing to specify the right parameters for TMIs also leads to flight delays, creating a significant obstacle in managing the increasing traffic volumes causing increased work load for the controllers. To address this issue, we propose the integration of Machine Learning (ML) models in the traffic flow management(TFM) pipeline. In current operations, decisions are made by human experts based on extensive training, historical patterns, available traffic and weather data. Since we have an abundance of data from past events that tell us the likely impact of various TMIs, by ingesting historical data, properly trained ML models can offer valuable insights and aid human decision-making. With the FAA increasingly exploring advanced analytics, ML emerges as a focal point for enhancing TFM within the National Airspace System (NAS). As a first step, this study aims to provide traffic controllers with decision-making support for the issuance and adjustment of TMIs. Data analytics and machine learning have been previously employed to address some of the challenges associated with TMIs. Numerous studies have concentrated on various facets of TMI issuance, exploring factors influencing TMI parameters, including arrival rate, airport capacity, and delay prediction. For example, using weather forecasts, several statistical methods were used to produce probabilistic capacity profiles which in conjunction with deterministic models provided insights into the GDP planning process [1–4]. The downside of using deterministic models is that they rely on fixed inputs and predetermined rules, which lack the ability to account for the inherent uncertainty and variability present in real-world scenarios. In a separate series of studies, researchers aimed to predict the occurrences of GDPs and GSs. The majority of these studies utilized various supervised learning methods, including Decision Trees, Naive Bayes, Support VectorMachines, and Random Forests to analyze the influence of weather conditions and arrival demand on TMI incidents[5–8]. However, these studies primarily focused on predicting the incidence of TMIs without explicitly addressing the scope of TMIs, including their duration and their geographical coverage. Furthermore, the emphasis of these studies was largely on GDPs, given their higher frequency and longer duration when compared to GSs. A limited number of studies focused on predicting the parameters of TMIs, specifically addressing their duration and extent. In one such study focusing on optimizing the TMI parameters at San Francisco International Airport (SFO),the authors utilized a probabilistic forecast of fog [9]. They simulated various capacity scenarios based on the (fog)burn-off forecasts, selecting GDP parameters that minimized airborne and overall ground delays. However, this approach exclusively emphasizes stratus (fog) burn-off as the primary determinant of GDP and GS, neglecting other influential factors like severe weather events, runway closures, lower capacity than traffic demand, and other important variables. Given the complexity of predicting the TMI and determining its scope, we seek a more holistic approach. We aim to consider all significant factors that could impact TMIs and their parameters. What sets this research apart is the fusion of all data sources relevant to the issuance and adjustment of TMIs and it represents the first comprehensive attempt to optimize TMIs in this manner. Since this comprehensive solution involves various aspects, we break down the problem into smaller components and input all parameters into a unified model called the “TMI Adjuster”. Figure 1 shows the overall framework and the list of datasets used in each model. The objective of the TMI Adjuster module is to deliver reliable, consistent and expedited recommendations for the progression, adjustment, and termination of TMIs. The ML solution entails developing a pipeline capable of predicting the necessity of a TMI (e.g., GS or GDP) along with its various parameters. For example, in the case of a GS, this includes the scope of the GS either in terms of distance from the destination airport or based on pre-defined airspace sectors. Here, scope refers to those regions and departing airports that are subject to the GS. In this paper, we concentrate on the issuance of GSs in the three major airports in the New York area — LaGuardia(LGA), John F. Kennedy International (JFK), and Newark Liberty International (EWR). We fuse traffic, weather and other relevant aviation data from years 2017 to 2019 to train and validate the ML models. In particular, we use the following datasets: •Terminal Aerodrome Forecast (TAF): meteorological forecasts specific to each airport, issued four times a day, covering predefined time periods. •TMI data: includes all GSs and GDPs along with their respective parameters. •Aviation System Performance Metrics (ASPM): includes traffic related data such as aircraft delays, arrival, and departure rates. •Notices to Airmen (NOTAMs): utilized to extract runway closure data and manage interdependencies between terminals in close proximity. •Flight cancellation data •Airspace Flow Programs (AFP): includes information on flight airborne holdings caused by TMIs. The data preprocessing entails transforming ASPM, TMI, AFP, NOTAMs, and weather data into an hourly format and consolidating all datasets by merging them based on date and time as the primary key. The TMI Adjuster framework comprises two parallel models: one dedicated to GS and a second model focused on GDP. As previously mentioned, our specific focus is on the GS model as a multi-classification problem. In this framework, each data point of the GS model input summarizes ten hours of data. Specifically, the data loader for the GS model generates the input and output of the model as follows: at a given time step, the input includes the actual traffic, weather, and TMI data from the two-hour window before the time step, alongside the weather forecast and scheduled traffic for the next 8 hours starting from the time step. Based on this information, the output of the GS model for each time interval consists of three dimensions. The first dimension represents a binary decision on whether there should be a GS in place for the next hour or not. The second dimension is related to the scope of the GS in the United States, and the third dimension is related to the scope of the GS in Canada (i.e., to determine if the GS impacts airports in Canada).One of the challenges with TMI modeling is the sparsity of TMI events, particularly regarding its scope. To address this challenge in the scope of the GS model output, we implement grouping. The GS scope for the US region is defined based on a list of centers that should be included when the GS is in place. With 20 centers in the US, we utilized historical data to group them into 4 categories. In particular, we summarized our historical data in a graph format where nodes represent centers, and link weights are defined based on the co-occurrence of centers in the scope parameter ofTMIs. By identified strongly connected components in this graph, we were able to partition the centers into four groups. We consider two model structures for the GS Model. Firstly, a hierarchical classification model [10], where the human decision-making for a GS is of hierarchical nature. The decision-maker first decides whether there is a need fora GS, and if the answer is yes, determines the scope. A hierarchical classification model organizes the problem into a class hierarchy, typically a tree or a Directed Acyclic Graph (DAG) structure, and considers the dependency of the decision in the previous step to the next component [10]. Here, we employ the local classifier per level approach, which involves training one multi-class classifier for each level of the class hierarchy. The second structure is the independent structure. In this setting, as the name suggests, we do not consider the dependency of the decisions in the different dimensions of the output of the model. Instead, for each dimension, we train a multi-class classifier independently. Table 1 summarizes GS model statistics for training, validation and testing. The table documents the effect of limiting data to the time steps when there was actually a TMI in place or when a TMI had just terminated. This resulted in a more balanced distribution of the GS class(GS positive class)versus “No GS”(GS negative class), which might help the training process. While JFK and LGA follow very similar distributions, with 40% and 42% GS positive class respectively, EWR has proportionally fewer GS incidents at 28%. Our subsequent phase involves evaluating the performance of both hierarchical structure and independent structure using different state-of-the-art multi-class classifier models such as Random Forest, Decision Trees, K-nearest Neighbors, and Logistic Regression and forecast the duration and scope of the GSs.

Farzan Masrour Shalmani↗

NASA NTRS2013

The Antarctic Search for Meteorites: A Model for Deep Space Exploration

In an era of shrinking buying power and reduced flight opportunities, NASA must extract the greatest possible value from all sources of insight into the future of human space exploration. Antarctica is one such source. The history of Antarctic exploration has many political and technical parallels with the development of space, and Antarctica's remoteness and harsh climate make it an excellent proxy for space (e.g., [1,2]). Links between exploration of space and of the Antarctic date back to the International Geophysical Year of 1957-1958, which saw both the launch of Sputnik 1 and the establishment of a station at the South Pole. The Antarctic Search for Meteorites (ANSMET) is an annual expedition to the south polar plateau to collect meteorites. Although its intent is not to simulate a space mission, the handful of astronauts who have participated in ANSMET agree that it is very similar to a long-duration space flight. Independently, NASA and other space agencies have simulated deep space exploration missions in "analog" activities at remote field sites on Earth (e.g., [3]). These include NASA Extreme Environment Mission Operations (NEEMO) [4,5], Desert Research And Technology Studies (Desert RATS) [6,7], and the Pavilion Lake Research Project (PLRP or simply Pavilion Lake) [8]. This report focuses on NEEMO, Desert RATS, and PLRP because of the author's firsthand experience with them. Other noteworthy analogs, such as the arctic Haughton Mars Project and the European Space Agency's underground Cooperative Adventure for Valuing and Exercising human behavior and performance Skills (CAVES), are not treated here. NASA analogs often include fully staffed control centers, astronauts serving as crew, and realistic mission timelines lasting one to two weeks. Analogs have provided key insights into system architectures and operational concepts for the future human exploration of deep space. They have pioneered techniques for human communication with significant speed-of-light delays, for conducting spacewalks on natural objects with negligible surface gravity, and for empowering exploration crews to work with reduced dependence on a ground control center. They have field-tested dozens of emerging technologies including spacewalking tools and full-scale prototype vehicles and habitats. They have provided valuable experience for astronauts preparing for their first space flight, and for flown crewmembers who will take command roles on later flights. Some analogs, especially PLRP, have connected observers in the field with science teams in remotely located control centers to produce high-quality, publishable scientific results. The analogs have accomplished all of this at a tiny fraction of the cost of an actual space flight. This report treats ANSMET as space flight analog. The chapter following this introduction describes ANSMET in depth. The report then presents data on logistics and crew considerations that may be useful for developers of future human space exploration missions. It offers detailed comparisons between ANSMET and past, present, and future space flights on the Space Shuttle, the International Space Station (ISS), and a proposed Mars mission. Those comparisons are intended to complement the work of Eppler [2], who compares ANSMET to the Apollo moon flights. This report also compares ANSMET with the Desert RATS, NEEMO, and PLRP analogs. It then presents observations and makes recommendations related to ANSMET's value as a simulated space mission. The report ends with a short conclusion. The remainder of this introductory chapter provides background material to help readers interpret the rest of the report. It gives brief overviews of Space Shuttle and ISS missions along with information on a notional future human flight to Mars. It also presents the general features of three of NASA's space flight "analog" projects. With those points of reference in place, the chapter concludes with an overview of ANSMET.

Love, Stanley G.↗

NASA NTRS2011

Introduction to: Atlantic Meridional Overturning Circulation(AMOC)

A striking conclusion of the Intergovernmental Panel on Climate Change 2007 report is the crucial role that the Atlantic Meridional Overturning Circulation (AMOC) may play in anthropogenic climate change. However, these IPCC coupled climate simulations show a broad range of uncertainty in the magnitude and timing of AMOC transport change ranging from none to nearly complete collapse within the 21st century. The potential consequences of large changes in the characteristics of AMOC have motivated the creation in the United States of an interagency program and implementation plan to develop monitoring and prediction capabilities for the AMOC This program parallels the development of substantial monitoring efforts by European, South American and African countries -- notably the UK Rapid and Rapid-Watch programs. The papers contained in this volume are derived from presentations at the First U.S. Atlantic Meridional Overturning Circulation (AMOC) Meeting held 4 - 6 May, 2009 to review the US implementation plan and its coordination with other monitoring activities. The Atlantic Meridional Overturning Circulation consists of multiple components illustrated in an attached figure. Water enters the South Atlantic at upper and intermediate depths through both western and eastern routes (where eddy transport is especially important) and is transported northward across the equator, where it recirculates within the northern subtropical and subpolar gyres. The northern end is defined by the sinking regions of the Nordic Seas and the Labrador Sea where the waters that eventually form the upper and lower branches of North Atlantic Deep Water are conditioned. High surface salinities, the result of high net evaporation in the tropics and subtropics (including the Mediterranean Sea), and presence of regions of the Arctic Ocean that remain ice-free even in winter allow for the rapid cooling and thus densification of surface water. This dense surface water becomes the source of deep water formation in the sinking regions. In addition to transporting mass, the AMOC transports roughly half of the total amount of heat carried northward through the northern subtropics (down the temperature-gradient) by the ocean. In contrast in the Southern Hemisphere AMOC transports heat up-gradient from the cool Circumpolar Current to the warm tropics. Paleoevidence suggests that AMOC heat transport in the two hemispheres has varied over time in ways intimately tied to millennial changes in the Earth's climate. In one example, the abrupt Younger Dryas spell of cold weather over the North Atlantic, which began 13,000 years ago, has generally been linked to a millennial shutdown of the AMOC as a result of massive freshwater discharge from the North American continent. The current AMOC monitoring array consists of a series of instrumented transects located across key passages (see Cunningham et al., 2010 for a recent review). In the Arctic and sub-Arctic, transects cross Fram Strait, Denmark Strait and the Faroe Channel (connecting Greenland, Iceland, and the United Kingdom), as well as the entrance to the Labrador Sea. Further south and extending outwards from the east coast of North America there are a series of monitoring arrays including arrays of the Canadian Atlantic Zone Monitoring Program, deployments of the Rapid Western Atlantic Variability Experiment (WAVE), Line W at 39 N, as well as the Rapid-MOC moored array. The latter spans the entire Atlantic basin along 26.5 N. At tropical latitudes we have the Meridional Overturning Variability Experiment (MOVE) array at 16 N, while in the Southern Hemisphere a corresponding basin-spanning transect is being established at the latitude of Cape of Good Hope, complemented by arrays at Drake Passage.

Hakkinen, Sirpa↗

NASA NTRS1999

Experimental Investigation of Pool Boiling Heat Transfer Enhancement in Microgravity in the Presence of Electric Fields

In boiling high heat fluxes are possible driven by relatively small temperature differences, which make its use increasingly attractive in aerospace applications. The objective of the research is to develop ways to overcome specific problems associated with boiling in the low gravity environment by substituting the buoyancy force with the electric force to enhance bubble removal from the heated surface. Previous studies indicate that in terrestrial applications nucleate boiling heat transfer can be increased by a factor of 50, as compared to values obtained for the same system without electric fields. The goal of our research is to experimentally explore the mechanisms responsible for EHD heat transfer enhancement in boiling in low gravity conditions, by visualizing the temperature distributions in the vicinity of the heated surface and around the bubble during boiling using real-time holographic interferometry (HI) combined with high-speed cinematography. In the first phase of the project the influence of the electric field on a single bubble is investigated. Pool boiling is simulated by injecting a single bubble through a nozzle into the subcooled liquid or into the thermal boundary layer developed along the flat heater surface. Since the exact location of bubble formation is known, the optical equipment can be aligned and focused accurately, which is an essential requirement for precision measurements of bubble shape, size and deformation, as well as the visualization of temperature fields by HI. The size of the bubble and the frequency of bubble departure can be controlled by suitable selection of nozzle diameter and mass flow rate of vapor. In this approach effects due to the presence of the electric field can be separated from effects caused by the temperature gradients in the thermal boundary layer. The influence of the thermal boundary layer can be investigated after activating the heater at a later stage of the research. For the visualization experiments a test cell was developed. All four vertical walls of the test cell are transparent, and they allow transillumination with laser light for visualization experiments by HI. The bottom electrode is a copper cylinder, which is electrically grounded. The copper block is heated with a resistive heater and it is equipped with 6 thermocouples that provide reference temperatures for the measurements with HI. The top electrode is a mesh electrode. Bubbles are injected with a syringe into the test cell through the bottom electrode. The working fluids presently used in the interferometric visualization experiments, water and PF 5052, satisfy requirements regarding thermophysical, optical and electrical properties. A 30kV power supply equipped with a voltmeter allows to apply the electric field to the electrodes during the experiments. The magnitude of the applied voltage can be adjusted either manually or through the LabVIEW data acquisition and control system connected to a PC. Temperatures of the heated block are recorded using type-T thermocouples, whose output is read by a data acquisition system. Images of the bubbles are recorded with 35mm photographic and 16mm high-speed cameras, scanned and analyzed using various software packages. Visualized temperature fields HI allows the visualization of temperature fields in the vicinity of bubbles during boiling in the form of fringes. Typical visualized temperature distributions around the air bubbles injected into the thermal boundary layer in PF5052 are shown. The temperature of the heated surface is 35 C. The temperature difference for a pair of fringes is approximately 0.05 C. The heat flux applied to the bottom surface is moderate, and the fringe patterns are regular. In the image a bubble penetrating the thermal boundary layer is visible. Because of the axial symmetry of the problem, simplified reconstruction techniques can be applied to recover the temperature field. The thermal plume developing above the heated surface for more intensive heating is shown. The temperature distribution in the liquid is clearly 3D, and tomographic techniques have to be applied to recover the temperature distribution in such a physical situation. A sequence of interferometric images showing the temperature distribution around the rising bubble, recorded with a high-speed camera is shown. Again, the temperature distribution is 3D, and a more complex approach to the evaluation, the tomographic reconstruction has to be taken. Measurement of the temperature distribution from the fringe pattern temperature distributions that yield important information regarding heat transfer are determined. Two algorithms that allow the quantitative evaluation of interferometric fringe patterns and the reconstruction of temperature fields during boiling have been developed at the Heat Transfer Laboratory of the Johns Hopkins University. In the first algorithm the bubble is assumed to be axially symmetrical, which significantly reduces the computational effort for quantifying the temperature distribution around the bubble. For this purpose the thermal boundary layer around the bubble is divided into equidistant concentric shells, and the refractive index is assumed to be constant in each of the shells. Since large temperature gradients are expected in the vicinity of the bubble during boiling, the deflection of the light beam cannot be neglected in boiling experiments. Since the exit angle of the light beam is known, this allows to account for the deflections and phase shifts outside the boundary layer (in the bulk fluid and in the windows of the test cell). Three dimensional temperature distributions in the vicinity of the bubble are reconstructed using tomographic techniques. In tomography, the measurement volume is sliced into 2D planes. In the present study these planes are parallel to the heated surface. The objective is to determine the values of the field parameter of interest in form of the field function in these 2D planes. The field parameter is the change of the refractive index of the liquid in the measurement volume caused by temperature changes. By superimposing data for many 2D planes recorded at the same time instant, the 3D temperature distribution in the measurement volume is recovered.

Herman, Cila↗