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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 OSTI2015

Impact of Network Activity Levels on the Performance of Passive Network Service Dependency Discovery

Network services often do not operate alone, but instead, depend on other services distributed throughout a network to correctly function. If a service fails, is disrupted, or degraded, it is likely to impair other services. The web of dependencies can be surprisingly complex---especially within a large enterprise network---and evolve with time. Acquiring, maintaining, and understanding dependency knowledge is critical for many network management and cyber defense activities. While automation can improve situation awareness for network operators and cyber practitioners, poor detection accuracy reduces their confidence and can complicate their roles. In this paper we rigorously study the effects of network activity levels on the detection accuracy of passive network-based service dependency discovery methods. The accuracy of all except for one method was inversely proportional to network activity levels. Our proposed cross correlation method was particularly robust to the influence of network activity. The proposed experimental treatment will further advance a more scientific evaluation of methods and provide the ability to determine their operational boundaries.

correlation↗
NASA NTRS2017

Hydrological Modeling of the Jezero Crater Outlet-Forming Flood

Abundant evidence exists for lakes on Mars both from orbital observations [e.g., 1-3] and in situ exploration [e.g., 4-5]. These lakes can be divided into two classes: those that were hydrologically closed, so their source valley(s) terminated at the basin [3], and those that were hydrologically open, where there was sufficient flow from inlet valley(s) to cause the lake to breach and form an outlet valley [2]. It is easier to be confident from orbital data alone that a standing body of water must have existed in open basins, because there is no other way for their perched outlet valleys to form. The majority of basins fed by valley networks, rather than by isolated inlet valleys, are open [6], with some important exceptions (e.g., Gale Crater). Jezero crater (Fig. 1) is one of the most well-studied open basin paleolakes on Mars, with a breach that re-mains well above the lowest part of the crater floor, and two sedimentary fans at its northwestern margin that are likely deltaic in origin [7-9]. CRISM observations of these sediments indicate they host a variety of alteration minerals [9-11], including smectite and carbonate, and both the mineralogy of the sediments and their settings suggest they have a strong potential for preserving organic materials [10]. As a result, Jezero is a strong candidate landing site for the Mars 2020 rover. Approximate formative discharges have been estimated for its well-preserved western fan (Q approximately 500m3/s) [7], but to our knowledge, no estimates for the dis-charges associated with formation and incision of its outlet valley have been presented. Indeed, only a few studies [e.g., 12-14] have attempted to reconstruct the formation of outlet breaches broadly similar to Jezero anywhere on Mars, despite the apparent commonality of basins with large outlets [e.g., 2]. The outlet valley formed as a dam breach when the lake overflowed. In such an event, the growth and incision of the breach is directly coupled to flood discharge. In the case of Jezero, the discharge through the breach eventually lacked the energy needed to erode through the dam further, preventing complete drainage of the lake. After the initial flood, further incision can take place if additional water flows into, and thus out of, the hydrologically open lake, though the rate of this erosion occurs under more typical fluvial conditions. Despite this qualitative understanding of the process, it is useful to explore numerically what range of model parameters are potentially consistent with obser-vations of the outlet. We ultimately seek to address questions that include: (1) What was the flood hydro-graph?, (2) What sediment transport processes were involved and what can we infer about the erosion process? (3) Can most or all of the Jezero outlet's morphology be explained as a consequence of catastrophic formation, or is additional longer-term erosion required?

geology↗
DOE OSTI2025

Machine learning guided search for energetically favorable metal borocarbide ternary compounds

In this work, we employ machine-learning (ML) combined with first principles calculations to efficiently search for the energetically favorable metal borocarbide (M-B-C) ternary compounds with M being the group 1–3 metal elements. Using a crystal graph convolutional neural network (CGCNN) ML approach followed by first-principles calculations, we predicted 47 energetically favorable stable and metastable ternary Na-B-C, Ca-B-C, and La-B-C ternary compounds with their decomposition energy (E d ) below or within 100 meV/atom from the currently known convex hulls. Phonon spectra and electronic structures of the 14 energetically favorable stable structures are also investigated by first-principles calculations. By substituting the metal atoms in the 29 energetically favorable non-equivalent template structures of Na (Ca, La)-B-C with other group 1–3 elements in the periodic table, we further obtain 22 stable structures and 52 metastable structures (E d ≤100 meV/atom with respect to the known convex hulls) for Li-B-C, K-B-C, Rb-B-C, Mg-B-C, Sr-B-C, Ba-B-C, Sc-B-C and Y-B-C ternary compounds. New convex hulls including our newly predicted stable ternary structures and the known stable structures are constructed for the M-B-C systems. The results obtained by our ML guided first-principles calculations enrich our knowledge in the structure and energy landscape of metal borocarbide ternary compounds and provide useful guidance for further experimental synthesis and discovery.

36 MATERIALS SCIENCE↗
NASA NTRS2019

Understanding Machine Learning in Earth Science: A Natural Language Processing Approach

Machine learning (ML) is being increasingly utilized in Earth science research. Benefits of ML include efficiency, reduction of human error, and ability to extract hidden patterns within data. However, the mutual lack of each other’s domain knowledge by ML and Earth science stands as a barrier to timely and effective implementation. Earth science, in particular, faces challenges in generating sample data, compared to those of traditional ML problems such as face recognition or stock predictions, where data is abundant and not lacking in ground truth, which is necessary for labeling. Earth science data are more varying in formats, such as HDF5 and image resolutions, and are not standardized across instruments, even within a given Earth science discipline. Previous studies have been done to outline the specific challenges that Earth science faces with ML, while others have focused on using existing publications to mine information efficiently. Other resources such as Scikit-Learn have developed decision trees for choosing appropriate machine learning algorithms, but application within Earth science subjects becomes much more complex. For the current study, we propose a methodology and tool that aids in implementation of ML in Earth science using natural language processing (NLP). Our work comprises three main parts: (1) analyzing existing publications related to ML and Earth science, using natural language processing: (2) extracting from the publications information on ML models subjects in Earth Science: and (3) visualizing the extracted relationships as a network graph. The resulting network graph should aid the Earth science communities in applying optimal ML algorithms and guiding data preparation through visualization of similar studies. The network graph and analysis of document similarity will be the basis of our next step, which is to develop a decision tree for selecting optimal machine learning methodologies for specified Earth science applications.

Zheng, Laura↗
NASA NTRS2010

The Process of the Development of an Operator

On the job training is where new employees called operators can start gaining knowledge on what they will be working on during their time in JSC. In these lessons I learned different things that are important ranging from thermal systems to electrical systems. While doing OJT classes the student will learn how to use a portable computer system which has displays that I also helped edit and clean up. The way you can also learn is by reading system briefs which describes the different systems. Due to the fact of a possible change in the ISS I updated a systems brief so that it can be relevant to what is actually on the space station. I was given a task that will help develop my skills and make myself better prepared for my future in the work field. The project that I worked on had me pulling real time data from the International Space Station. The Data I obtained from the space station will be correlated to battery performance. The group I will be working which is called REBA and we will take the telemetry and evaluate the data. I will be working with my mentor Ben Chislom and co-op Tyler along with the Pro team. They then will put this data into a graph so that they can get the discrepancies and find a way to improve the battery performance. The first weeks I read familiarization books that informed me how the ISS works, how it was built, and the systems that are used to keep the station working. This project is going to benefit NASA by finding out how electricity is being used on the ISS and enabling us to see how it can be used more efficiently. This way we can operate the ISS without wasting power. While conducting research that goes on inside the space station knowing all electricity is being used efficiently.

Banks, Terrence↗
DOE OSTI2016

Automatic segmentation of the glenohumeral cartilages from magnetic resonance images

Purpose: Magnetic resonance (MR) imaging plays a key role in investigating early degenerative disorders and traumatic injuries of the glenohumeral cartilages. Subtle morphometric and biochemical changes of potential relevance to clinical diagnosis, treatment planning, and evaluation can be assessed from measurements derived from in vivo MR segmentation of the cartilages. However, segmentation of the glenohumeral cartilages, using approaches spanning manual to automated methods, is technically challenging, due to their thin, curved structure and overlapping intensities of surrounding tissues. Automatic segmentation of the glenohumeral cartilages from MR imaging is not at the same level compared to the weight-bearing knee and hip joint cartilages despite the potential applications with respect to clinical investigation of shoulder disorders. In this work, the authors present a fully automated segmentation method for the glenohumeral cartilages using MR images of healthy shoulders. Methods: The method involves automated segmentation of the humerus and scapula bones using 3D active shape models, the extraction of the expected bone–cartilage interface, and cartilage segmentation using a graph-based method. The cartilage segmentation uses localization, patient specific tissue estimation, and a model of the cartilage thickness variation. The accuracy of this method was experimentally validated using a leave-one-out scheme on a database of MR images acquired from 44 asymptomatic subjects with a true fast imaging with steady state precession sequence on a 3 T scanner (Siemens Trio) using a dedicated shoulder coil. The automated results were compared to manual segmentations from two experts (an experienced radiographer and an experienced musculoskeletal anatomist) using the Dice similarity coefficient (DSC) and mean absolute surface distance (MASD) metrics. Results: Accurate and precise bone segmentations were achieved with mean DSC of 0.98 and 0.93 for the humeral head and glenoid fossa, respectively. Mean DSC scores of 0.74 and 0.72 were obtained for the humeral and glenoid cartilage volumes, respectively. The manual interobserver reliability evaluated by DSC was 0.80 ± 0.03 and 0.76 ± 0.04 for the two cartilages, implying that the automated results were within an acceptable 10% difference. The MASD between the automatic and the corresponding manual cartilage segmentations was less than 0.4 mm (previous studies reported mean cartilage thickness of 1.3 mm). Conclusions: This work shows the feasibility of volumetric segmentation and separation of the glenohumeral cartilages from MR images. To their knowledge, this is the first fully automated algorithm for volumetric segmentation of the individual glenohumeral cartilages from MR images. The approach was validated against manual segmentations from experienced analysts. In future work, the approach will be validated on imaging datasets acquired with various MR contrasts in patients.

60 APPLIED LIFE SCIENCES↗
NASA NTRSDate not supplied

Development of A Directed Acyclic Graph for Venous Thromboembolism During Spaceflight

Introduction: Recent studies have reported the development of venous blood flow stasis in astronauts and an occlusive venous thrombosis during spaceflight. Subsequent investigations revealed approximately one quarter of surveilled crew members had some degree of blood flow stasis in the left internal jugular vein. Therefore, NASA’s Human System Risk Board now formally tracks venous thromboembolism (VTE) as a “concern” for human spaceflight. To investigate potential mechanisms by which exposures concomitant with spaceflight (e.g., microgravity, radiation) may contribute to VTE, we developed a causal diagram in the form of a directed acyclic graph (DAG). Methods: The mechanisms by which spaceflight exposures may elevate the risk of VTE and the downstream effects on mission outcomes were critically analyzed, taking into account scientific literature and subject matter expertise consultation, and a DAG was generated. A Level-of-Evidence score for each causal relationship was assigned based on assessing the literature against a set of criteria derived from the A. Bradford Hill Causal Guidelines. Results: The set of three main factors that predispose people to VTE (hypercoagulability, endothelial damage, and blood stasis) is known as Virchow’s Triad. In constructing the DAG for VTE we articulated various mechanisms by which the principal spaceflight hazards (microgravity, radiation, closed hostile environment, isolation and confinement, distance from Earth) are thought to interact with or cause the components in Virchow’s triad. We found sufficient evidence to at least speculate that fluid shifts from microgravity, compensatory alterations in hematologic indices, spaceflight atmospheric conditions, and oxidative stress/inflammation from radiation may be potential contributors to VTE development. Discussion: Developing the DAG entailed a systematic and repeatable approach for visualizing relationships between contributing factors that may lead to VTE in spaceflight. Articulating pathways linking spaceflight exposures to VTE risk factors and possible VTE development enables subject matter experts from different domains to construct a shared mental model. Assignment of levels of evidence scores to the relationships helps identify knowledge and capability gaps that should be considered for further investigation. Furthermore, the DAG highlights modifiable variables and may therefore facilitate the development of new VTE risk mitigation strategies.

Alexander Svoronos↗
NASA NTRS2016

Augmenting Parametric Optimal Ascent Trajectory Modeling with Graph Theory

It has been well documented that decisions made in the early stages of Conceptual and Pre-Conceptual design commit up to 80% of total Life-Cycle Cost (LCC) while engineers know the least about the product they are designing [1]. Once within Preliminary and Detailed design however, making changes to the design becomes far more difficult to enact in both cost and schedule. Primarily this has been due to a lack of detailed data usually uncovered later during the Preliminary and Detailed design phases. In our current budget-constrained environment, making decisions within Conceptual and Pre-Conceptual design which minimize LCC while meeting requirements is paramount to a program's success. Within the arena of launch vehicle design, optimizing the ascent trajectory is critical for minimizing the costs present within such concerns as propellant, aerodynamic, aeroheating, and acceleration loads while meeting requirements such as payload delivered to a desired orbit. In order to optimize the vehicle design its constraints and requirements must be known, however as the design cycle proceeds it is all but inevitable that the conditions will change. Upon that change, the previously optimized trajectory may no longer be optimal, or meet design requirements. The current paradigm for adjusting to these updates is generating point solutions for every change in the design's requirements [2]. This can be a tedious, time-consuming task as changes in virtually any piece of a launch vehicle's design can have a disproportionately large effect on the ascent trajectory, as the solution space of the trajectory optimization problem is both non-linear and multimodal [3]. In addition, an industry standard tool, Program to Optimize Simulated Trajectories (POST), requires an expert analyst to produce simulated trajectories that are feasible and optimal [4]. In a previous publication the authors presented a method for combatting these challenges [5]. In order to bring more detailed information into Conceptual and Pre-Conceptual design, knowledge of the effects originating from changes to the vehicle must be calculated. In order to do this, a model capable of quantitatively describing any vehicle within the entire design space under consideration must be constructed. This model must be based upon analysis of acceptable fidelity, which in this work comes from POST. Design space interrogation can be achieved with surrogate modeling, a parametric, polynomial equation representing a tool. A surrogate model must be informed by data from the tool with enough points to represent the solution space for the chosen number of variables with an acceptable level of error. Therefore, Design Of Experiments (DOE) is used to select points within the design space to maximize information gained on the design space while minimizing number of data points required. To represent a design space with a non-trivial number of variable parameters the number of points required still represent an amount of work which would take an inordinate amount of time via the current paradigm of manual analysis, and so an automated method was developed. The best practices of expert trajectory analysts working within NASA Marshall's Advanced Concepts Office (ACO) were implemented within a tool called multiPOST. These practices include how to use the output data from a previous run of POST to inform the next, determining whether a trajectory solution is feasible from a real-world perspective, and how to handle program execution errors. The tool was then augmented with multiprocessing capability to enable analysis on multiple trajectories simultaneously, allowing throughput to scale with available computational resources. In this update to the previous work the authors discuss issues with the method and solutions.

Patrick D Dees↗
DOE OSTI2022

Transportation Energy Data Book (Edition 40)

The Transportation Energy Data Book: Edition 40 is a statistical compendium prepared and published by Oak Ridge National Laboratory (ORNL) under contract with the U.S. Department of Energy, Office of Energy Efficiency and Renewable Energy, Vehicle Technologies Office. Designed for use as a desk-top reference, the Data Book represents an assembly and display of statistics and information that characterize transportation activity and presents data on other factors that influence transportation energy use. The purpose of this document is to present relevant statistical data in the form of tables and graphs. The latest edition of the Data Book is available via the Internet (tedb.ornl.gov).This edition of the Data Book has 13 chapters which focus on various aspects of the transportation industry. Chapter 1 focuses on petroleum; Chapter 2 – energy; Chapter 3 – highway vehicles; Chapter 4 – light vehicles; Chapter 5 – heavy vehicles; Chapter 6 – alternative fuel vehicles; Chapter 7 – transit and other shared mobility; Chapter 8 – fleet vehicles; Chapter 9 – household vehicles; Chapter 10 – nonhighway modes; Chapter 11 – transportation and the economy; Chapter 12 – greenhouse gas emissions; and Chapter 13 – criteria pollutant emissions. The sources used represent the latest available data. There are also two appendices which include detailed source information for some tables and measures of conversion. A glossary of terms is also included for the reader’s convenience.

02 PETROLEUM↗
DOE OSTI2020

Determining flow directions in river channel networks using planform morphology and topology

Abstract. The abundance of global, remotely sensed surface water observations has accelerated efforts toward characterizing and modeling how water moves across the Earth's surface through complex channel networks. In particular, deltas and braided river channel networks may contain thousands of links that route water, sediment, and nutrients across landscapes. In order to model flows through channel networks and characterize network structure, the direction of flow for each link within the network must be known. In this work, we propose a rapid, automatic, and objective method to identify flow directions for all links of a channel network using only remotely sensed imagery and knowledge of the network's inlet and outlet locations. We designed a suite of direction-predicting algorithms (DPAs), each of which exploits a particular morphologic characteristic of the channel network to provide a prediction of a link's flow direction. DPAs were chained together to create “recipes”, or algorithms that set all the flow directions of a channel network. Separate recipes were built for deltas and braided rivers and applied to seven delta and two braided river channel networks. Across all nine channel networks, the recipe-predicted flow directions agreed with expert judgement for 97 % of all tested links, and most disagreements were attributed to unusual channel network topologies that can easily be accounted for by pre-seeding critical links with known flow directions. Our results highlight the (non)universality of process–form relationships across deltas and braided rivers.

54 ENVIRONMENTAL SCIENCES↗
NASA NTRS1993

An experimental study of the sources of fluctuating pressure loads beneath swept shock/boundary-layer interactions

An experimental research program providing basic knowledge and establishing a database on the fluctuating pressure loads produced on aerodynamic surfaces beneath three dimensional shock wave/boundary layer interactions is described. Such loads constitute a fundamental problem of critical concern to future supersonic and hypersonic flight vehicles. A turbulent boundary layer on a flat plate is subjected to interactions with swept planar shock waves generated by sharp fins at angle of attack. Fin angles from 10 to 20 deg at freestream Mach numbers of 3 and 4 produce a variety of interaction strengths from weak to very strong. Miniature Kulite pressure transducers flush-mounted in the flat plate are used to measure interaction-induced wall pressure fluctuations. The distributions of properties of the pressure fluctuations, such as their ring levels, amplitude distributions, and power spectra, are also determined. Measurements were made for the first time in the aft regions of these interactions, revealing fluctuating pressure levels as high as 160 dB. These fluctuations are dominated by low frequency (0-5 kHz) signals. The maximum ring levels in the interactions show an increasing trend with increasing interaction strength. On the other hand, the maximum ring levels in the forward portion of the interactions decrease linearly with increasing interaction sweep back. These ring pressure distributions and spectra are correlated with the features of the interaction flowfield. The unsteadiness of the off-surface flowfield is studied using a new, non-intrusive technique based on the shadow graph method. The results indicate that the entire lambda-shock structure generated by the interaction undergoes relatively low-frequency oscillations. Some regions where particularly strong fluctuations are generated were identified. Fluctuating pressure measurements are also made along the line of symmetry of an axisymmetric jet impinging upon a flat plate at an angle. This flow was chosen as a simple analog to the impinging jet region found in the rear portion of the shock wave/boundary layer interactions under study. It is found that a sharp peak in ring pressure level exists at or near the mean stagnation point. It is suggested that the phenomena responsible for this peak may be active in the swept interactions as well, and may cause the extremely high fluctuating pressures observed in the impinging jet region in the present experimental program.

Settles, G. S.↗
NASA NTRS1993

Cognitive engineering models in space systems

NASA space systems, including mission operations on the ground and in space, are complex, dynamic, predominantly automated systems in which the human operator is a supervisory controller. Models of cognitive functions in complex systems are needed to describe human performance and form the theoretical basis of operator workstation design, including displays, controls, and decision aids. Currently, there several candidate modeling methodologies. They include the Rasmussen abstraction/aggregation hierarchy and decision ladder, the goal-means network, the problem behavior graph, and the operator function model. The research conducted under the sponsorship of this grant focuses on the extension of the theoretical structure of the operator function model and its application to NASA Johnson mission operations and space station applications. The initial portion of this research consists of two parts. The first is a series of technical exchanges between NASA Johnson and Georgia Tech researchers. The purpose is to identify candidate applications for the current operator function model; prospects include mission operations and the Data Management System Testbed. The second portion will address extensions of the operator function model to tailor it to the specific needs of Johnson applications. At this point, we have accomplished two things. During a series of conversations with JSC researchers, we have defined the technical goal of the research supported by this grant to be the structural definition of the operator function model and its computer implementation, OFMspert. Both the OFM and OFMspert have matured to the point that they require infrastructure to facilitate use by researchers not involved in the evolution of the tools. The second accomplishment this year was the identification of the Payload Deployment and Retrieval System (PDRS) as a candidate system for the case study. In conjunction with government and contractor personnel in the Human-Computer Interaction Lab, the PDRS was identified as the most accessible system for the demonstration. Pursuant to this a PDRS simulation was obtained from the HCIL and an initial knowledge engineering effort was conducted to understand the operator's tasks in the PDRS application. The preliminary results of the knowledge engineering effort and an initial formulation of an operator function model (OFM) are contained in the appendices.

Mitchell, Christine M.↗
DOE OSTI2022

Illuminating the pathways to carbon liberation: a systems approach to characterizing the consequential unknowns of carbon transformation and loss from thawing permafrost peatlands (Final Report)

The IsoGenie3 Project delivered new systems-level insights into carbon cycling in thawing permafrost landscapes, with an emphasis on methane and carbon dioxide emissions. From >200 samples from the site collected over a decade, co-analyzed for geochemistry and microbiology, the team recovered ~1,500 assembled microbial genomes and ~1,900 viral population genomes, revealing appreciable genetic novelty - from a new highly abundant bacterial phylum, to novel methane consumers and their activities, to rampant viral novelty. IsoGenie3 linked these organisms to carbon compound transformations (which define the cycling of organic matter in soils, and the loss of the greenhouse gases carbon dioxide and methane), and saw that the microbes at each stage of permafrost thaw had different genetic potential to degrade categories of compounds, expressed that genetic potential differently, and actually transformed carbon compounds into greenhouse gases in different ways. IsoGenie 3 identified that some of the thaw-stage differences were due to plant-microbiome relationships; the plant species across the thaw gradient contributed different carbon compounds into the soil, and hosted distinct microbiota (differing among parts of plants as well as species). Lastly, microbes in the saturated post-thaw conditions appeared likely to contribute to the mobilization and toxification of mercury released during thaw. In parallel with ongoing field sampling and analysis, hypotheses arising from field observations were tested via lab incubation experiments. When communities are taken out of their native habitats, they behave differently, and the team first rigorously quantified the magnitude of this effect on microbiome composition and functional capacity, organic matter composition, and gas production; overall the main system processes were maintained in the lab incubations under the conditions tested. Further, the microbial data could inform geochemical reaction network models of those processes. Then, the team ran experiments with additions of compounds, varying temperature, and “live” vs. “dead” peat (the latter having been gamma irradiated, with a few additional variants to control for methodological artifacts). From these, we (a) determined the importance of plant-derived soluble phenolic compounds in bogs’ extraordinary recalcitrance of organic matter, and carbon gas emissions skewed to carbon dioxide; (b) proposed an abiotic ‘tanning’ mechanism, which could contribute to Sphagnum’s inhibitory effect on anaerobic decomposition through alteration of N availability. IsoGenie3 illuminated longer-term and landscape-scale interactions of permafrost thaw and carbon cycling, advancing knowledge of the drivers of methane dynamics not only across in the permafrost-associated peatland (where hydrology and plant communities dictate microbiomes) but also their interconnected lakes (where sediment carbon quality and resident microbiota are determined by position within lake, and lake features). By leveraging observations of site methane dynamics extending well before this project, the team was able to construct a 44-year portrait of the interplay of permafrost thaw, hydrology, vegetation dynamics, and carbon gas emissions, and the doubling of the fully-thawed fens over this time. From the detailed study of this focal site, IsoGenie3 also aimed to improve model representation of these kinds of sites and processes. To improve predictions of methane transformations, we incorporated acetate and isotope dynamics into the ‘DNDC’ biogeochemistry model. In addition, recovered genomes were grouped into ‘functional groups’, i.e. the genomes that perform a specific function of interest, then used to parameterize maximum growth rate and optimum growth temperature (via signatures in their sequence composition) for the BioCrunch model. The BioCrunch model was then in turn used to test the impact of increasing functional resolution of the microbes, on the carbon gas emissions. Lastly for modeling, the ecosys model was parameterized from the microbial and other data, and used to evaluate drivers of e.g. change in methane emissions. Finally, this project also led to the development of a range of new methods and tools, a new metric of organic matter decomposability, as well as a graph-database solution to multidisciplinary data storage and querying. This project’s ongoing analyses at our focal site also contributed to broader advancements in understanding elements of genetic plasticity and methane metabolism, climate change microbiology and community assembly, global peatland geochemistry and Arctic lakes’ roles in climate feedbacks.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2018

Xi-cam : a versatile interface for data visualization and analysis

Xi-cam is an extensible platform for data management, analysis and visualization. Xi-cam aims to provide a flexible and extensible approach to synchrotron data treatment as a solution to rising demands for high-volume/high-throughput processing pipelines. The core of Xi-cam is an extensible plugin-based graphical user interface platform which provides users with an interactive interface to processing algorithms. Plugins are available for SAXS/WAXS/GISAXS/GIWAXS, tomography and NEXAFS data. With Xi-cam 's `advanced' mode, data processing steps are designed as a graph-based workflow, which can be executed live, locally or remotely. Remote execution utilizes high-performance computing or de-localized resources, allowing for the effective reduction of high-throughput data. Xi-cam 's plugin-based architecture targets cross-facility and cross-technique collaborative development, in support of multi-modal analysis. Xi-cam is open-source and cross-platform, and available for download on GitHub.

Pandolfi, Ronald J. (ORCID:0000000308248548)↗
NASA NTRS2002

Science opportunity analyzer - a multi-mission tool for planning

For many years the diverse scientific community that supports JPL's wide variety ofinterplanetary space missions has needed a tool in order to plan and develop their experiments. The tool needs to be easily adapted to various mission types and portable to the user community. The Science Opportunity Analyzer, SOA, now in its third year of development, is intended to meet this need. SOA is a java-based application that is designed to enable scientists to identify and analyze opportunities for science observations from spacecraft. It differs from other planning tools in that it does not require an in-depth knowledge of the spacecraft command system or operation modes to begin high level planning. Users can, however, develop increasingly detailed levels of design. SOA consists of six major functions: Opportunity Search, Visualization, Observation Design, Constraint Checking, Data Output and Communications. Opportunity Search is a GUI driven interface to existing search engines that can be used to identify times when a spacecraft is in a specific geometrical relationship with other bodies in the solar system. This function can be used for advanced mission planning as well as for making last minute adjustments to mission sequences in response to trajectory modifications. Visualization is a key aspect of SOA. The user can view observation opportunities in either a 3D representation or as a 2D map projection. The user is given extensive flexibility to customize what is displayed in the view. Observation Design allows the user to orient the spacecraft and visualize the projection of the instrument field of view for that orientation using the same views as Opportunity Search. Constraint Checking is provided to validate various geometrical and physical aspects of an observation design. The user has the ability to easily create custom rules or to use official project-generated flight rules. This capability may also allow scientists to easily impact the cost to science if flight rule changes occur. Data Output generates information based on the spacecraft's trajectory, opportunity search results or based on a created observation. The data can be viewed either in tabular format or as a graph. Finally, SOA is unique in that it is designed to be able to communicate with a variety of existing planning and sequencing tools. From the very beginning SOA was designed with the user in mind. Extensive surveys of the potential user community were conducted in order to develop the software requirements. Throughout the development period, close ties have been maintained with the science community to insure that the tool maintains its user focus. Although development is still in its early stages, SOA is already developing a user community on the Cassini project, which is depending on this tool for their science planning. There are other tools at JPL that do various pieces of what SOA can do; however, there is no other tool which combines all these functions and presents them to the user in such a convenient, cohesive, and easy to use fashion.

SOA science planning mission operations sequence s↗
NASA NTRS1999

A Study of Direct and Cloud-Mediated Radiative Forcing of Climate Due to Aerosols

The Intergovernmental Panel on Climate Change (IPCC) has reported that in the southeastern US and eastern China, the general greenhouse warming due to anthropogenic gaseous emissions is dominated by the cooling effect of anthropogenic aerosols. To verify this model prediction in eastern China and southeastern US, we analyzed regional patterns of climate changes at 72 stations in eastern China during 1951- 94 (44 years), and at 52 stations in the southeastern US during 1949-94 (46 years) to detect the fingerprint of aerosol radiative forcing. It was found that the mean rates of change of annual mean daily, maximum, minimum temperatures and diurnal temperature range (DTR) in eastern China were 0.8, -0.2, 1.8, and -2.0 C/100 years respectively, while the mean rates of change of annual mean daily, maximum, minimum temperatures and DTR in the southeastern US were -0.2, -0.6, 0.2, and -0.8 C/100 years, respectively. This indicates that the high rate of increase in annual mean minimum temperature in eastern China results in a slightly warming trend of daily temperature, while the high rate of decrease in annual mean maximum temperature and low rate of increase in annual mean minimum temperature lead to the cooling trend of daily temperature in the southeastern US. We found that the warming from the longwave forcing due to both greenhouse gases and aerosols was completely counteracted by the shortwave aerosol forcing in the southeastern US in the past 46 years. A slightly overall warming trend in eastern China is evident; winters have become milder. This finding is explained by hypothesizing that increasing energy usage during the past 44 years has resulted in more coal and biomass burning, thus increasing the emission of absorbing soot and organic aerosols in eastern China. Such emissions, in addition to well-known Asia dust and greenhouse gases, may be responsible for the winter warming trend in eastern China that we have reported here. The sensitivity of aerosol radiative properties to aerosol composition, size distribution, relative humidity (RH) is examined for the following aerosol systems: inorganic and organic ions (Cl-, Br-, NO3 -, SO4 2-, Na+, NH4 +, K+, Ca2+, Mg2+, HCOO-, CH3COO-, CH3CH2COO-, CH3COCOO-, OOCCOO2-, MSA-1); water-insoluble inorganic and organic compounds (elemental carbon, n-alkanes, SiO2, Al2O3, Fe2O3 and other organic compounds). The partial molar refraction method was used to calculate the real part of the refractive index. It was found that the asymmetry factor increased by approximately 48% with the real part varying from 1.40 to 1.65, and the single scattering albedo decreased by 24% with the imaginary part varying from -0.005 to -0.1. The asymmetry factor increased by 5.4 times with the geometric standard deviation varying from 1.2 to 3.0. The radiation transmission is very sensitive to the change in size distribution; other factors are not as significant. To determine the aerosol direct radiative forcing (ADRF), the aerosol optical depth (AOD) values at the three operational wavelengths (415, 500 and 673 nm) were determined at a regionally representative site, namely, Mt. Gibbs (35.78 deg N, 82.29 deg W, elevation 2006 m) in Mt. Mitchell State Park, NC, and a site located in an adjacent valley (Black Mountain, 35.66 deg N, 82.38 deg W, elevation 951 m) in the southeastern US. The two sites are separated horizontally by 10 km and vertically by 1 km. It was found that the representative total AOD values at 500 nm at the valley site for highly polluted (HP), marine (M) and continental (C) air masses were 0.68 +/- 0.33, 0.29 +/- 0.19 and 0.10 +/- 0.04, respectively. A search-graph method was used to retrieve the columnar size distribution (number concentration N, effective radius reff and geometric standard deviation=?g) from the optical depth observations at three operational wavelengths. The ground albedo, single scattering albedo and imaginary part of the refractive index were calculated using a mathematically unique procedure involving a Mie code and a radiative transfer code in conjunction with the retrieved aerosol size distribution, AOD, and diffuse-direct irradiance ratio. It was found that N, r(eff) and sigma(g) were in the ranges of 10 to 1.7 x 10(exp 4)/cubic cm, 0.09 to 0.68 micrometers and 1.12 to 2.95, respectively. The asymmetry factor and single scattering albedo were in the ranges of 0.63 to 0.75 and 0.74 to 0.97 respectively. The ground albedo for the forested terrain and imaginary part of refractive index were found to be in the ranges of 0.06 to 0.29 and 0.005 to 0.051 respectively. On the basis of these aerosol radiative properties obtained at the research sites and computations using the Column Radiation Model (CRM) of National Center of Atmospheric Research (NCAR) Community Climate Model (CCM3), it was found that the average cloud-free 24-hour ADRF values were -13 +/- 8, -8 +/- 3, -33 +/- 16 W/square m for marine, continental, and polluted air masses, respectively. On the assumption that the fractional coverage of clouds is 0.61, it was estimated that the annual mean ADRF was 7 +/- 2 W/square m in the southeastern US. The review with respect to the current knowledge of organic acids shows that aerosol formate and acetate concentrations range from 0.02 to 5.3 nmol/cubic m and from 0.03 to 12.4 nmol/cubic m respectively, and that between 34% to 77% of formate and between 21% to 66% of acetate are present in the fine fraction of aerosols. It was found that although most (98-99%) of these volatile organic acids were present in the gas phase, their concentrations in the aerosol particles were sufficient to make them a good candidate for cloud condensation nuclei (CCN). It is hypothesized that organic acids are at least one of the primary sources of CCN in the atmosphere due to their ubiquitous presence in the troposphere, especially over the continental forested areas. The results of our measurements at Palmer Station, Antarctica show that the daily average CCN concentrations at 0.3% and 1% supersaturations ranged from 0.3 to 160/cubic cm and from 4 to 168/cubic cm, respectively, during the period from 17 January to 26 February, 1994. New evidence for substantial and definitive CCN enhancement near and within cloud has been observed at Mt. Mitchell, North Carolina. The results show that the average monthly CCN concentrations were 460 +/- 217, 386 +/- 286, 429 +/- 228 and 238 +/- 134/cubic cm for in-cloud, overcast, clear and rainy conditions, respectively. The typical CCN spectra show that there were a lot of small CCN produced and the ion concentrations (especially H+ and SO4 2-) were very high during the CCN enhancement period. The significantly positive correlation between black carbon (BC) and CCN at 1% supersaturation indicates that a percentage of the BC measured at the site may be in the form of an internal mixture and participated in the formation of CCN.

Yu, Shao-Cai↗
NASA NTRS2000

A Tool for Automatic Data Distribution for CFD Applications on Structured Grids

Development of HPF versions of NPB and ARC3D has shown that HPF provides an efficient, concise way to express parallelism and to organize data traffic. The use of HPF, as noted in the papers, requires an intimate knowledge of the applications and a detailed analysis of data affinity, data movement, and data granularity. To simplify and accelerate the task of developing HPF versions of existing CFD applications we have designed and implemented ADAPT (Automatic Data Alignment and Placement Tool). ADAPT analyzes a CFD application working on a single structured grid and generates HPF TEMPLATE, (RE)DISTRIBUTION, ALIGNMENT, and INDEPENDENT directives. The directives can be generated on the nest level, subroutine level, application level, or on the application interface level. ADAPT annotates an existing CFD FORTRAN application, performing computations on single or multiple grids. On each grid the application is considered as a sequence of operators, each applied to a set of variables defined in a particular grid domain. ADAPT automatically detects implicit operators (i.e., having data dependences) and explicit operators (without data dependences). For parallelization of an explicit operator ADAPT creates a template for the operator domain, aligns arrays used in the operator with the template, distributes the template, and declares the loops over the distributed dimensions as INDEPENDENT. For parallelization of an implicit operator, the distribution of the operator's domain should be consistent with the operator's dependences. Any dependence between sections distributed on different processors would preclude parallelization if the compiler does not have an ability to pipeline computations. If a data distribution is "orthogonal" to the dependences of an implicit operator, then the loop which implements the operator can be declared as INDEPENDENT. ADAPT starts with an analysis of array index expressions of the loop nests. For each pair of arrays referenced in an assignment statement, it generates an arc in the alignment graph and annotates it with an affinity relation. The template, alignment, and distribution directives for a particular loop nest are then derived from a transitive closure of the affinity relation. A compromise of data distributions in different nests and subroutines is achieved by merging annotated alignment graphs for adjacent nests/stibroutine calls in the nest/call graph of the application in the process called distribution lifting. ADAPT has been implemented as a C++ program running in conjunction with a parallelization tool called CAPTools. ADAPT uses the parse tree, interprocedural analysis and application database generated by CAPTools. It also uses the Directed Graph class, initially implemented in p2d2 (parallel debugger oi distributed programs), and some other classes supporting symbolic computations. ADAPT uses data distribution techniques described. ADAPT was tested with ARC3D and the FT benchmark and has demonstrated a code performance within a factor of 1.5 of handwritten versions.

Frumkin, Michael↗