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Jones, Jeremy

Publications and source records attributed to Jones, Jeremy.

At least 19 records

Climate, Hydrology, and Nutrients Control the Seasonality of Si Concentrations in Rivers

Abstract The seasonal behavior of fluvial dissolved silica (DSi) concentrations, termedDSi regime, mediates the timing of DSi delivery to downstream waters and thus governs river biogeochemical function and aquatic community condition. Previous work identified five distinct DSi regimes across rivers spanning the Northern Hemisphere, with many rivers exhibiting multiple DSi regimes over time. Several potential drivers of DSi regime behavior have been identified at small scales, including climate, land cover, and lithology, and yet the large‐scale spatiotemporal controls on DSi regimes have not been identified. We evaluate the role of environmental variables on the behavior of DSi regimes in nearly 200 rivers across the Northern Hemisphere using random forest models. Our models aim to elucidate the controls that give rise to (a) average DSi regime behavior, (b) interannual variability in DSi regime behavior (i.e., Annual DSi regime), and (c) controls on DSi regime shape (i.e., minimum and maximum DSi concentrations). Average DSi regime behavior across the period of record was classified accurately 59% of the time, whereas Annual DSi regime behavior was classified accurately 80% of the time. Climate and primary productivity variables were important in predicting Average DSi regime behavior, whereas climate and hydrologic variables were important in predicting Annual DSi regime behavior. Median nitrogen and phosphorus concentrations were important drivers of minimum and maximum DSi concentrations, indicating that these macronutrients may be important for seasonal DSi drawdown and rebound. Our findings demonstrate that fluctuations in climate, hydrology, and nutrient availability of rivers shape the temporal availability of fluvial DSi.

Environmental Sciences & Ecology↗

Recycling Perspectives of Electric Arc Furnace Slag in the United States: A Review

This article presents a comprehensive review of electric arc furnace (EAF) slag recycling in the United States, examining its classification and the associated challenges and opportunities of its industrial use. The study affirms EAF slag's nonhazardous status. Here, the main challenges identified in EAF slag applications include substantial variations in composition and volume instability during/after hydration. Analysis of the U.S. recycling practices reveals that EAF slag is predominantly reused, with minimal landfill disposal. However, its prevalent use as a low value-added aggregate in construction applications underscores the industry's ongoing challenge to get additional value from EAF slag recycling. Despite these challenges, the study highlights a great potential for increased value extraction from EAF slag recycling. Beyond conventional applications as a clinker material for the cement industry, the review explores modern technologies for steelmaking slag recycling, revealing options for recovering valuable metals such as Cr, V, Mo, and Fe through methods such as leaching, reduction, and oxidation.

42 ENGINEERING↗

Cyber-Informed Engineering Implementation Guide: Version 1.0 [Slides]

This Implementation Guide describes the principles of Cyber-Informed Engineering (CIE) and outlines questions that engineering teams should consider during each phase of a system's lifecycle to effectively employ these principles. It describes what it means to engineer systems in a cyber-informed way, rather than offering a comprehensive, step-by-step process or procedure for CIE implementation. This guide complements - but does not replace - the application of cybersecurity standards or practices currently in place within an organization. Engineers and technicians that design critical energy infrastructure installations can use this Implementation Guide to integrate the 12 principles of CIE into each phase of the engineering lifecycle, from concept to retirement. The guide is aimed at system or design engineers, rather than software engineers or operational cybersecurity practitioners. The engineers who design, build, operate, and maintain the physical infrastructure are best positioned to leverage a system's engineering design to diminish the severity of cyber attacks or digital technology failures. CIE expands cybersecurity decisions into the engineering space, not by asking engineers to become cyber experts, but by calling on engineers to apply engineering tools and make engineering decisions that improve cybersecurity outcomes. CIE examines the engineering consequences that a sophisticated cyber attacker could achieve and drives engineering changes that may provide deterministic mitigations to limit or eliminate those consequences.

24 POWER TRANSMISSION AND DISTRIBUTION↗

Cassini Orbit Determination Performance (July 2008 - December 2011)

This paper reports on the orbit determination performance for the Cassini spacecraft from July 2008 to December 2011. During this period, Cassini made 85 revolutions around Saturn and had 52 close satellite encounters. 35 of those were with the massive Titan, 13 with the small, yet interesting, Enceladus as well as 2 with Rhea and 2 with Dione. The period also includes 4 double encounters, where engineers had to plan the trajectory for two close satellite encounters within days of each other at once. Navigation performance is characterized by ephemeris errors relative to in-flight predictions. Most Titan encounters 3-dimensional results are within a 1.5 formal sigma, with a few exceptions, mostly attributable to larger maneuver execution errors. Results for almost all other satellite encounter reconstructions are less than 3 sigma from their predictions. The errors are attributable to satellite ephemerides errors and in some cases to maneuver execution errors.

navigation performance↗

Maneuver Automation Software

The Maneuver Automation Software (MAS) automates the process of generating commands for maneuvers to keep the spacecraft of the Cassini-Huygens mission on a predetermined prime mission trajectory. Before MAS became available, a team of approximately 10 members had to work about two weeks to design, test, and implement each maneuver in a process that involved running many maneuver-related application programs and then serially handing off data products to other parts of the team. MAS enables a three-member team to design, test, and implement a maneuver in about one-half hour after Navigation has process-tracking data. MAS accepts more than 60 parameters and 22 files as input directly from users. MAS consists of Practical Extraction and Reporting Language (PERL) scripts that link, sequence, and execute the maneuver- related application programs: "Pushing a single button" on a graphical user interface causes MAS to run navigation programs that design a maneuver; programs that create sequences of commands to execute the maneuver on the spacecraft; and a program that generates predictions about maneuver performance and generates reports and other files that enable users to quickly review and verify the maneuver design. MAS can also generate presentation materials, initiate electronic command request forms, and archive all data products for future reference.

Uffelman, Hal↗

Infrastructure for Rapid Development of Java GUI Programs

The Java Application Shell (JAS) is a software framework that accelerates the development of Java graphical-user-interface (GUI) application programs by enabling the reuse of common, proven GUI elements, as distinguished from writing custom code for GUI elements. JAS is a software infrastructure upon which Java interactive application programs and graphical user interfaces (GUIs) for those programs can be built as sets of plug-ins. JAS provides an application- programming interface that is extensible by application-specific plugins that describe and encapsulate both specifications of a GUI and application-specific functionality tied to the specified GUI elements. The desired GUI elements are specified in Extensible Markup Language (XML) descriptions instead of in compiled code. JAS reads and interprets these descriptions, then creates and configures a corresponding GUI from a standard set of generic, reusable GUI elements. These elements are then attached (again, according to the XML descriptions) to application-specific compiled code and scripts. An application program constructed by use of JAS as its core can be extended by writing new plug-ins and replacing existing plug-ins. Thus, JAS solves many problems that Java programmers generally solve anew for each project, thereby reducing development and testing time.

Jones, Jeremy↗

Preparing for the Huygens Probe Mission, Cassini orbit determination results for the first and second targeted Titan encounters

Dynamic modeling of the spacecraft and Saturn system, tracking data, including radio-metric and optical navigation data, and measurement modeling associated with the final trajectory analysis are described. Navigation predictions produced during the operational phase are compared with the final trajectory in order to gain insight into navigation performance and maneuver execution errors. Special attention is given to refinement of the dynamical environment of Saturn, particularly Titan, during the first two orbits.

navigation↗

Using automated planning for sensorweb response

This paper describes efforts to link these science event detection systems with an automated response system to retarget remote sensing assets to observe these important but transient science events. Of course, automated mission planning is a key element of the overall tracking and response system. We describe the current prototype system which utilizes the Earth Observing One spacecraft, MODIS flying on Terra and Aqua, QuickSCAT, GOES, and AVHRR platforms as well as future plans for expansion.

sensorweb response↗

Autonomous Multi-Sensor Coordination: The Science Goal Monitor

Many dramatic earth phenomena are dynamic and coupled. In order to fully understand them, we need to obtain timely coordinated multi-sensor observations from widely dispersed instruments. Such a dynamic observing system must include the ability to Schedule flexibly and react autonomously to sciencehser driven events; Understand higher-level goals of a sciencehser defined campaign; Coordinate various space-based and ground-based resources/sensors effectively and efficiently to achieve goals. In order to capture transient events, such a 'sensor web' system must have an automated reactive capability built into its scientific operations. To do this, we must overcome a number of challenges inherent in infusing autonomy. The Science Goal Monitor (SGM) is a prototype software tool being developed to explore the nature of automation necessary to enable dynamic observing. The tools being developed in SGM improve our ability to autonomously monitor multiple independent sensors and coordinate reactions to better observe dynamic phenomena. The SGM system enables users to specify what to look for and how to react in descriptive rather than technical terms. The system monitors streams of data to identify occurrences of the key events previously specified by the scientisther. When an event occurs, the system autonomously coordinates the execution of the users' desired reactions between different sensors. The information can be used to rapidly respond to a variety of fast temporal events. Investigators will no longer have to rely on after-the-fact data analysis to determine what happened. Our paper describes a series of prototype demonstrations that we have developed using SGM and NASA's Earth Observing-1 (EO-1) satellite and Earth Observing Systems' Aqua/Terra spacecrafts' MODIS instrument. Our demonstrations show the promise of coordinating data from different sources, analyzing the data for a relevant event, autonomously updating and rapidly obtaining a follow-on relevant image. SGM was used to investigate forest fires, floods and volcanic eruptions. We are now identifying new Earth science scenarios that will have more complex SGM reasoning. By developing and testing a prototype in an operational environment, we are also establishing and gathering metrics to gauge the success of automating science campaigns.

Koratkar, Anuradha↗

Cassini tour navigation strategy

The Cassini-Huygens spacecraft was launched on October 15, 1997 as a joint NASA/ESA mission to explore Saturn. After a 7 year cruise the spacecraft will enter orbit around Saturn on 1 July 2004 for a 4 year investigation of the Saturnian system. The Cassini Navigation Team is responsible for designing the reference trajectory and conducting operations to realize this design. This paper describes the strategy for achieving project requirements, the characteristics of the Cassini navigation challenge, and the underlying assumptions.

Saturn↗

Cassini tour navigation strategy

This paper describes the strategy for achieving project requirements, the characteristics of the Cassini navigation challenge, and the underlying assumptions.

Cassini↗

Science Goal Driven Automation for NASA Missions: The Science Goal Monitor

Infusion of automation technologies into NASA s future missions will be essential not only to achieve substantial reduction in mission operations staff and costs, but also in order to both effectively handle an exponentially increasing volume of scientific data and to successfully meet dynamic, opportunistic scientific goals and objectives. Current spacecraft operations cannot respond to science driven events, such as intrinsically variable or short-lived phenomena in a timely manner. For such investigations, we must teach our platforms to dynamically understand, recognize, and react to the scientists goals. While much effort has gone into automating routine spacecraft operations to reduce human workload and hence costs, applying intelligent automation to the science side, i.e., science data acquisition, data analysis and reactions to that data analysis in a timely and still scientifically valid manner, has been relatively under-emphasized.

Korathkar, Anuradha↗