Results for “data- limited” — Page 85

NASA NTRSDate not supplied

NASA Delay Tolerant Networks: Operational, Evolving, an Ready for Expansion

The future of humanity’s presence beyond Earth depends on the successful commercialization of space. For commercialization to succeed, companies need cost-efficient architectures to support their business models and minimize risks for human capital, design, development, and operations. An ongoing challenge to any space enterprise is the reality that terrestrial network technologies are insufficient to provide reliable communications between assets in space. Whether you need to ensure your valuable data is safely transmitted to the ground or reliably delivered between platforms in orbit, ensuring data integrity over intermittent communication links is a necessity. Current solutions to space communications rely heavily on manual recording, storing, and retrieval of data from spacecraft. The current standard in space communication protocols, Consultative Committee for Space Data Systems (CCSDS) Space Packet standard, is reliant on inflexible network architectures based around mission-critical infrastructure to ensure data delivery. However, by automating the recording, storing, retrieval, and verification of data with Delay Tolerant Networks (DTN), the operator is freed from the dependence on manual data management and expensive mission critical infrastructure. NASA has been developing delay tolerant systems since the late 1990’s. Multiple DTN implementations have been established during that time, each suited to different use cases. Most notably, the DTN deployment for the International Space Station (ISS) includes demonstration of two DTN technologies: Interplanetary Overlay Network (ION) and Delay Tolerant Network Marshall Enterprise (DTNME). Beyond ISS, there are even more NASA DTN deployments being considered. Now that DTN implementations are maturing, it is appropriate to reflect upon these decades of work, review the integration and performance of the existing ISS deployment, and explore the future possibilities for DTN deployment industry-wide. The ISS DTN deployment is a complex architecture consisting of different DTN implementations for the onboard and ground network environments. The ION DTN implementation is being used in the on-board network. The Huntsville Operations Support Center (HOSC) DTN implementation, DTNME, is used by the ground network supporting ISS and will soon be a second onboard gateway too. The two implementations work cooperatively to provide high fidelity data services to flight operations users and payload developers across the globe. Though the two implementations yield a quality service, limitations are evident. Data rate, data storage, and device management are constrained by the services themselves and the complex nature of the deployment. Evolution of operations concepts will improve system capabilities and stability, but significant improvement will require additional development to the implementations themselves and to the overall deployment architecture. Taking advantage of the ongoing development and operation of the ISS DTN service will be central to the success of the future evolutions of NASA DTN deployments while demonstrating the benefits of DTN’s low-cost reliable data communication protocols for the growing commercial space industry. A broad effort on DTN integration and support is necessary to promote expansion beyond existing applications. NASA is developing several useful DTN implementations across a number of different systems: ION, DTNME, High-Rate DTN (HDTN), Bundle Protocol Library (BPLib), and others. To prevent fragmentation, DTN implementation teams need to communicate, collaborate, and integrate with one another to build a solid operational foundation for new DTN deployments. The establishment of a group that can assist new DTN users with understanding the purpose of each DTN implementation, provide best practices, and serve as a general knowledge base is paramount. Potential use of DTN on Gateway and other future NASA missions further drives the need for streamlined communication between DTN implementation teams. A well-integrated and highly engaged NASA DTN working group should help provide system architects the best DTN solutions for future commercial space efforts. This paper will first review the history of DTN implementations, explore the shortcoming of current space networking solutions given available limits in technology, and therefore establish the need for Delay Tolerant Networking in space communications. Secondly, the authors will explore NASA’s array of DTN implementations and highlight their usefulness to space applications. Thirdly, this paper will establish general DTN implementation distinguishing factors. Fourthly, the authors will discuss attempts to create a generic DTN comparison matrix, and the authors will review potential future topics in DTN innovation and collaboration, highlighting several key future efforts. Finally, this paper will describe how the institution of a NASA DTN Working Group will benefit DTN adoption across the governmental and commercial space sector. The goal of this paper is to encourage enthusiasm for DTN, share strategies for improving DTN on both current and future applications, promote the collaboration of DTN implementation groups within the international space operations community, and open the conversations about DTN, priorities, complexities, and innovation to the wider spaceflight industry.

DTN↗

NASA NTRSDate not supplied

NASA Delay Tolerant Networks: Operational, Evolving, an Ready for Expansion

The future of humanity’s presence beyond Earth depends on the successful commercialization of space. For commercialization to succeed, companies need cost-efficient architectures to support their business models and minimize risks for human capital, design, development, and operations. An ongoing challenge to any space enterprise is the reality that terrestrial network technologies are insufficient to provide reliable communications between assets in space. Whether you need to ensure your valuable data is safely transmitted to the ground or reliably delivered between platforms in orbit, ensuring data integrity over intermittent communication links is a necessity. Current solutions to space communications rely heavily on manual recording, storing, and retrieval of data from spacecraft. The current standard in space communication protocols, Consultative Committee for Space Data Systems (CCSDS) Space Packet standard, is reliant on inflexible network architectures based around mission-critical infrastructure to ensure data delivery. However, by automating the recording, storing, retrieval, and verification of data with Delay Tolerant Networks (DTN), the operator is freed from the dependence on manual data management and expensive mission critical infrastructure. NASA has been developing delay tolerant systems since the late 1990’s. Multiple DTN implementations have been established during that time, each suited to different use cases. Most notably, the DTN deployment for the International Space Station (ISS) includes demonstration of two DTN technologies: Interplanetary Overlay Network (ION) and Delay Tolerant Network Marshall Enterprise (DTNME). Beyond ISS, there are even more NASA DTN deployments being considered. Now that DTN implementations are maturing, it is appropriate to reflect upon these decades of work, review the integration and performance of the existing ISS deployment, and explore the future possibilities for DTN deployment industry-wide. The ISS DTN deployment is a complex architecture consisting of different DTN implementations for the onboard and ground network environments. The ION DTN implementation is being used in the on-board network. The Huntsville Operations Support Center (HOSC) DTN implementation, DTNME, is used by the ground network supporting ISS and will soon be a second onboard gateway too. The two implementations work cooperatively to provide high fidelity data services to flight operations users and payload developers across the globe. Though the two implementations yield a quality service, limitations are evident. Data rate, data storage, and device management are constrained by the services themselves and the complex nature of the deployment. Evolution of operations concepts will improve system capabilities and stability, but significant improvement will require additional development to the implementations themselves and to the overall deployment architecture. Taking advantage of the ongoing development and operation of the ISS DTN service will be central to the success of the future evolutions of NASA DTN deployments while demonstrating the benefits of DTN’s low-cost reliable data communication protocols for the growing commercial space industry. A broad effort on DTN integration and support is necessary to promote expansion beyond existing applications. NASA is developing several useful DTN implementations across a number of different systems: ION, DTNME, High-Rate DTN (HDTN), Bundle Protocol Library (BPLib), and others. To prevent fragmentation, DTN implementation teams need to communicate, collaborate, and integrate with one another to build a solid operational foundation for new DTN deployments. The establishment of a group that can assist new DTN users with understanding the purpose of each DTN implementation, provide best practices, and serve as a general knowledge base is paramount. Potential use of DTN on Gateway and other future NASA missions further drives the need for streamlined communication between DTN implementation teams. A well-integrated and highly engaged NASA DTN working group should help provide system architects the best DTN solutions for future commercial space efforts. This paper will first review the history of DTN implementations, explore the shortcoming of current space networking solutions given available limits in technology, and therefore establish the need for Delay Tolerant Networking in space communications. Secondly, the authors will explore NASA’s array of DTN implementations and highlight their usefulness to space applications. Thirdly, this paper will establish general DTN implementation distinguishing factors. Fourthly, the authors will discuss attempts to create a generic DTN comparison matrix, and the authors will review potential future topics in DTN innovation and collaboration, highlighting several key future efforts. Finally, this paper will describe how the institution of a NASA DTN Working Group will benefit DTN adoption across the governmental and commercial space sector. The goal of this paper is to encourage enthusiasm for DTN, share strategies for improving DTN on both current and future applications, promote the collaboration of DTN implementation groups within the international space operations community, and open the conversations about DTN, priorities, complexities, and innovation to the wider spaceflight industry.

DTN↗

DOE OSTI2020

Optically targeted search for gravitational waves emitted by core-collapse supernovae during the first and second observing runs of advanced LIGO and advanced Virgo

In this work, we present the results from a search for gravitational-wave transients associated with core-collapse supernovae observed within a source distance of approximately 20 Mpc during the first and second observing runs of Advanced LIGO and Advanced Virgo. No significant gravitational-wave candidate was detected. We report the detection efficiencies as a function of the distance for waveforms derived from multidimensional numerical simulations and phenomenological extreme emission models. Furthermore, the sources with neutrino-driven explosions are detectable at the distances approaching 5 kpc, and for magnetorotationally driven explosions the distances are up to 54 kpc. However, waveforms for extreme emission models are detectable up to 28 Mpc. For the first time, the gravitational-wave data enabled us to exclude part of the parameter spaces of two extreme emission models with confidence up to 83%, limited by coincident data coverage. Besides, using ad hoc harmonic signals windowed with Gaussian envelopes, we constrained the gravitational-wave energy emitted during core collapse at the levels of 4.27×10 -4 M ⊙ c 2 and 1.28×10 -1 M ⊙ c 2 for emissions at 235 and 1304 Hz, respectively. These constraints are 2 orders of magnitude more stringent than previously derived in the corresponding analysis using initial LIGO, initial Virgo, and GEO 600 data.

79 ASTRONOMY AND ASTROPHYSICS↗

DOE OSTI2024

FunM2C: A Filter for Uncertainty Visualization of Multivariate Data on Multi-Core Devices

Uncertainty visualization is an emerging research topic in data visualization because neglecting uncertainty in visualization can lead to inaccurate assessments. In this paper, we study the propagation of multivariate data uncertainty in visualization. Although there have been a few advancements in probabilistic uncertainty visualization of multivariate data, three critical challenges remain to be addressed. First, the state-of-the-art probabilistic uncertainty visualization framework is limited to bivariate data (two variables). Second, existing uncertainty visualization algorithms use computationally intensive techniques and lack support for cross-platform portability. Third, as a consequence of the computational expense, integration into production visualization tools is impractical. In this work, we address all three issues and make a threefold contribution. First, we take a step to generalize the state-of-the-art probabilistic framework for bivariate data to multivariate data with an arbitrary number of variables. Second, through utilization of VTK-m’s shared-memory parallelism and cross-platform compatibility features, we demonstrate acceleration of multivariate uncertainty visualization on different many-core architectures, including OpenMP and AMD GPUs. Third, we demonstrate the integration of our algorithms with the ParaView software. We demonstrate the utility of our algorithms through experiments on multivariate simulation data with three and four variables.

Hari, Gautam↗

NASA NTRS1986

MST data exchange through the NCAR incoherent-scatter radar data base

One means of making MST (mesosphere stratosphere troposphere) radar data more easily accessible for scientific research by the general scientific community is through a centralized data base. Such a data base can be designed to readily provide information on data availability and quality, and to provide copies of data from any radar in a common format to the user. The ionospheric incoherent scatter community has established a centralized data base at NCAR that may serve not only as a model for a possible MST data base, but also as a catalyst for getting an MST data base started. (Some key elements of the NCAR data base are given.) The NCAR data base can include MST data in the same framework with relatively little extra effort. They are willing to handle MST data on a limited basis in order to permit assessment of community interest and in order to provide some experience with a centralized data base for MST data.

Richmond, A. D.↗

NASA NTRS2020

Optically targeted search for gravitational waves emitted by core-collapse supernovae during the first and second observing runs of advanced LIGO and advanced Virgo

We present the results from a search for gravitational-wave transients associated with core-collapse supernovae observed within a source distance of approximately 20 Mpc during the first and second observing runs of Advanced LIGO and Advanced Virgo. No significant gravitational-wave candidate was detected. We report the detection efficiencies as a function of the distance for waveforms derived from multidimensional numerical simulations and phenomenological extreme emission models. The sources with neutrino-driven explosions are detectable at the distances approaching 5 kpc, and for magnetorotationally driven explosions the distances are up to 54 kpc. However, waveforms for extreme emission models are detectable up to 28 Mpc. For the first time, the gravitational-wave data enabled us to exclude part of the parameter spaces of two extreme emission models with confidence up to 83%, limited by coincident data coverage. Besides, using ad hoc harmonic signals windowed with Gaussian envelopes, we constrained the gravitational-wave energy emitted during core collapse at the levels of 4.27 × 10^(−4) Mꙩc^(2) and 1.28 × 10^(−1) Mꙩc^(2) for emissions at 235 and 1304 Hz, respectively. These constraints are 2 orders of magnitude more stringent than previously derived in the corresponding analysis using initial LIGO, initial Virgo, and GEO 600 data.

B. P. Abbott↗

NASA NTRS2022

Revolutionizing Our Understanding of Particle Energization in Space Plasmas Using on-Board Wave-Particle Correlator Instrumentation

A leap forward in our understanding of particle energization in plasmas throughout the heliosphere is essential to answer longstanding questions in heliophysics, including the heating of the solar corona, acceleration of the solar wind, and energization of particles that lead to observable phenomena, such as the Earth’s aurora. The low densities and high temperatures of typical heliospheric environments lead to weakly collisional plasma conditions. Under these conditions, the energization of particles occurs primarily through collisionless interactions between the electromagnetic fields and the individual plasma particles with energies characteristic of a particular interaction. To understand how the plasma heating and particle acceleration impacts the macroscopic evolution of the heliosphere, impacting phenomena such as extreme space weather, it is critical to understand these collisionless wave-particle interactions on the characteristic ion and electron kinetic timescales. Such understanding requires high-cadence measurements of both the electromagnetic fields and the three-dimensional particle velocity distributions. Although existing instrument technology enables these measurements, a major challenge to maximize the scientific return from these measurements is the limited amount of data that can be transmitted to the ground due to telemetry constraints. A valuable, but underutilized, approach to overcome this limitation is to compute on-board correlations of the maximum-cadence field and particle measurements to improve the sampling time by several orders of magnitude. Here we review the fundamentals of the innovative field-particle correlation technique, present a formulation of the technique that can be implemented as an on-board wave-particle correlator, and estimate results that can be achieved with existing instrumental capabilities for particle velocity distribution measurements.

plasma heating↗

NASA NTRSDate not supplied

Physics-Guided Deep Learning for Complex System Health Management and Decision Making

The landscape of complex engineered systems is rapidly evolving, from smart manufacturing facilities to next-generation transportation vehicles. As these systems become increasingly sophisticated and interconnected, the need for advanced health management systems grows ever more critical. These systems must go beyond simple monitoring, actively predicting potential failures before they occur. This paradigm shift from fixed maintenance schedules to condition-based predictions is key to optimizing system performance, enhancing safety, and paving the way for autonomous decision-making across various industries. Whether in industrial processes, energy systems, or advanced transportation, the ability to anticipate and prevent failures is becoming a cornerstone of operational excellence. To accurately predict the future health of any complex system, knowledge of its current health state and future operational conditions is essential. Recent advancements in data-driven algorithms have generated growing interest in artificial intelligence for industrial applications. However, the limitations of pure data-driven methods, particularly in industries where data acquisition is costly and limited, have become apparent. This has led to a focus on blending physics with data-driven algorithms, mitigating the drawbacks of both approaches while emphasizing their respective advantages. This research proposes a novel framework for integrating physics-based performance models with deep learning algorithms for the prognostics of complex safety-critical systems. In this approach, physics-based models serve as a blueprint, capturing fundamental system behaviors, while deep learning algorithms, leveraging real-world sensor data, fill in gaps and identify subtle patterns indicative of potential problems. This hybrid methodology, utilizing techniques such as Physics-Informed Neural Networks (PINNs), offers a powerful solution for predicting system health. By fusing domain knowledge with data-driven insights, this approach promises more accurate, adaptable, and reliable models for health prediction. The resulting framework is versatile, applicable across various sectors including aerospace, manufacturing, and energy systems, ultimately contributing to safer, more efficient operations in our increasingly complex technological landscape.

Diagnostics↗

DOE OSTI2024

Improving the Discovery Power of the Dark Energy Survey Gravitational Wave Program in Its Fourth Observing Campaign

The universe is growing at an accelerated rate, yet the several experiments and science cases used to measure this property yield conflicting results for the rate. Known colloquially as the Hubble tension problem, this discrepancy calls for a novel measurement of the Hubble Constant, H0, in order to be resolved. The Dark Energy Survey Gravitational Wave group (DESGW) aims to relieve this tension by performing a standard sirens measurement of H0 independent of traditional methods. To do so in the current era of data abundance and limited telescope time demands a robust, optimized, and complete science software pipeline to carefully balance the transition from gravitational wave data to state-of-the-art images, images to photometric data, and photometric data to identification and analysis of electromagnetic counterparts to gravitational wave signals. This thesis details the contributions of the author to the DESGW Search & Discovery Pipeline for the fourth observing run of the LIGO/Virgo/KAGRA gravitational wave detector network, as well as the science applications that have been pursued.

79 ASTRONOMY AND ASTROPHYSICS↗

NASA NTRS2006

Multilayered Clouds Identification and Retrieval for CERES Using MODIS

Traditionally, analyses of satellite data have been limited to interpreting the radiances in terms of single layer clouds. Generally, this results in significant errors in the retrieved properties for multilayered cloud systems. Two techniques for detecting overlapped clouds and retrieving the cloud properties using satellite data are explored to help address the need for better quantification of cloud vertical structure. The first technique was developed using multispectral imager data with secondary imager products (infrared brightness temperature differences, BTD). The other method uses microwave (MWR) data. The use of BTD, the 11-12 micrometer brightness temperature difference, in conjunction with tau, the retrieved visible optical depth, was suggested by Kawamoto et al. (2001) and used by Pavlonis et al. (2004) as a means to detect multilayered clouds. Combining visible (VIS; 0.65 micrometer) and infrared (IR) retrievals of cloud properties with microwave (MW) retrievals of cloud water temperature Tw and liquid water path LWP retrieved from satellite microwave imagers appears to be a fruitful approach for detecting and retrieving overlapped clouds (Lin et al., 1998, Ho et al., 2003, Huang et al., 2005). The BTD method is limited to optically thin cirrus over low clouds, while the MWR method is limited to ocean areas only. With the availability of VIS and IR data from the Moderate Resolution Imaging Spectroradiometer (MODIS) and MW data from the Advanced Microwave Scanning Radiometer EOS (AMSR-E), both on Aqua, it is now possible to examine both approaches simultaneously. This paper explores the use of the BTD method as applied to MODIS and AMSR-E data taken from the Aqua satellite over non-polar ocean surfaces.

Sun-Mack, Sunny↗

DOE OSTI2026

Impact of Crystalline Phases on Low-Activity Waste Glass Durability: Insights from PCT and VHT

During vitrification of nuclear wastes, slow cooling along the container centerline promotes crystalline phase formation, which can alter residual glass composition and reduce chemical durability. This study investigates the effects of crystalline phases on the chemical durability of low-activity waste (LAW) borosilicate glasses using the product consistency test (PCT) and vapor hydration test (VHT) on container centerline cooled (CCC) samples. A preliminary model (R2 = 0.88) was developed to predict CCC PCT responses based on glass composition, PCT data from quenched glasses, and measured crystal fractions. Using the latest LAW glass dataset, the feasibility of predictive modeling is evaluated, limitations in current data and methods are identified, and challenges for improving model accuracy are discussed to guide future data collection and model development.

borosilicate glass↗

NASA NTRS1978

Determination of volume fraction in multiphase systems using incomplete pole figures

The determination of the volume fraction of a second phase in a multiphase sample by X-ray diffraction becomes more difficult if the diffracting planes have a preferred orientation. Lopata and Kula have described a method of treating this problem using complete pole figures for each of the phases. With some samples, it is not always possible or convenient to obtain data over the full hemisphere. Equations and an example are given which require X-ray data over a limited range of approximately 0 to 75 deg. This can be obtained by reflection without a specially cut sample or transmission data. A series of Legendre polynomials are fitted to data collected while spinning the sample about its normal. An extrapolation is made possible by introducing two conditions on the end points which must be satisfied if the extrapolation functions are to be valid.

Houska, C. R.↗

NASA NTRS1981

Wireless, in-vessel neutron monitor for initial core-loading of advanced breeder reactors

An experimental wireless, in-vessel neutron monitor was developed to measure the reactivity of an advanced breeder reactor as the core is loaded for the first time to preclude an accidental critically incident. The environment is liquid sodium at a temperature of approx. 220 C, with negligible gamma or neutron radiation. With ultrasonic transmission of neutron data, no fundamental limitation was observed after tests at 230 C for 2000 h. The neutron sensitivity was approx. 1 count/s-nv, and the potential data transmission rate was approx. 10,000 counts/s.

Delorenzo, J. T.↗

NASA NTRS2005

Intelligent Systems: Terrestrial Observation and Prediction Using Remote Sensing Data

NASA has made science and technology investments to better utilize its large space-borne remote sensing data holdings of the Earth. With the launch of Terra, NASA created a data-rich environment where the challenge is to fully utilize the data collected from EOS however, despite unprecedented amounts of observed data, there is a need for increasing the frequency, resolution, and diversity of observations. Current terrestrial models that use remote sensing data were constructed in a relatively data and compute limited era and do not take full advantage of on-line learning methods and assimilation techniques that can exploit these data. NASA has invested in visualization, data mining and knowledge discovery methods which have facilitated data exploitation, but these methods are insufficient for improving Earth science models that have extensive background knowledge nor do these methods refine understanding of complex processes. Investing in interdisciplinary teams that include computational scientists can lead to new models and systems for online operation and analysis of data that can autonomously improve in prediction skill over time.

Coughlan, Joseph C.↗

NASA NTRS2015

A Historical Review of Cermet Fuel Development and the Engine Performance Implications

This paper reviews test data for cermet fuel samples developed in the 1960's to better quantify Nuclear Thermal Propulsion (NTP) cermet engine performance, and to better understand contemporary fuel testing results. Over 200 cermet (W-UO2) samples were tested by thermally cycling to 2500 deg (2770 K) in hydrogen. The data indicates two issues at high temperatures: the vaporization rate of UO2 and the chemical stability of UO2. The data show that cladding and chemical stabilizers each result in large, order of magnitude improvements in high temperature performance, while other approaches yield smaller, incremental improvements. Data is very limited above 2770 K, and this complicates predictions of engine performance at high Isp. The paper considers how this material performance data translates into engine performance. In particular, the location of maximum temperature within the fuel element and the effect of heat deposition rate are examined.

Ceramic Nuclear Fuel↗

NASA NTRSDate not supplied

Flight Trajectory Prediction Based on Hybrid-Recurrent Networks

The development of future technologies for the National Airspace System (NAS) will be reliant on a new communications infrastructure capable of managing the limited available spectrum for communications among aircraft and ground systems. Emerging approaches to autonomous allocation of aviation spectrum mostlyrely on machine learning techniques, where 4D (longitude, latitude, altitude, time) trajectory prediction is an important data input to enable real-time resource allocation. This study explores and evaluates effective data sources and deep recurrent neural network techniques when determining flight trajectories. Specifically, data are collected and evaluated in a 100-day and 14-day period. Sources of data include NASA Sherlock Data Warehouse, MIT Lincoln Labs Corridor Integrated Weather Service (CIWS), and assorted NOAA weather datasets. Deep learning models for 4D predictions all utilize a hybrid-recurrent technique. A baseline model is considered via the convolutional-LSTM design from the existing literature. The modified design considers Gated Recurrent Units (GRU), Independently Recurrent Neural Networks (IndRNN), and stand-alone self-attention layers. Results indicatethe effectiveness of LSTM and GRUcells for state-of-the-art data processing (interpolation). Additionally, GRUs may be quickly trained with limited data, allowing for exacting improvements with optimizer selection. Attention mechanisms provide notable performance improvements to convolutional layers and may extend dimensional capabilities of a learning model. Finally, NOAA measurements provide only a supplemental value, requiring support from tailored measurements for Air Traffic Management.

Nathan Schimpf↗

DOE OSTI2022

Search for hidden-charm tetraquark with strangeness in e + e - → $K$ + $D^{}_{s}$ - $D$ 0 + c.c.*

We report a search for a heavier partner of the recently observed Z cs (3985) - state, denoted as $Z^{'-}_{cs}$, in the process e + e - → $K$ + $D^{*}_{s}$ - $D$ *0 + c.c., based on e + e - collision data collected at the center-of-mass energies of $\sqrt{s}$ = 4.661, 4.682 and 4.699 GeV with the BESIII detector. The $Z^{'-}_{cs}$ is of interest as it is expected to be a candidate for a hidden-charm and open-strange tetraquark. A partial-reconstruction technique is used to isolate K + recoil-mass spectra, which are probed for a potential contribution from $Z^{'-}_{cs}$ → $D^{*}_{s}$ - $D$ *0 + (c.c.). We find an excess of $Z^{'-}_{cs}$ → $D^{*}_{s}$ - $D$ *0 + (c.c.) candidates with a significance of 2.1σ, after considering systematic uncertainties, at a mass of 4123.5 ± 0.7 stat. ± 4.7 syst. ) MeV/c 2 . As the data set is limited in size, the upper limits are evaluated at the 90% confidence level on the product of the Born cross sections (σ BORN ) and the branching fraction ($\mathcal{B}$) of $Z^{'-}_{cs}$ → $D^{*}_{s}$ - $D$ *0 , under different assumptions of the $Z^{'-}_{cs}$ mass from 4.120 to 4.140 MeV and of the width from 10 to 50 MeV at the three center-of-mass energies. The upper limits of σ BORN ∙ $\mathcal{B}$ are found to be at the level of $\mathcal{O}$(1) pb at each energy. Larger data samples are needed to confirm the $Z^{'-}_{cs}$ state and clarify its nature in the coming years.

73 NUCLEAR PHYSICS AND RADIATION PHYSICS↗

NASA NTRS1982

Hydrology team

General problems faced by hydrologists when using historical records, real time data, statistical analysis, and system simulation in providing quantitative information on the temporal and spatial distribution of water are related to the limitations of these data. Major problem areas requiring multispectral imaging-based research to improve hydrology models involve: evapotranspiration rates and soil moisture dynamics for large areas; the three dimensional characteristics of bodies of water; flooding in wetlands; snow water equivalents; runoff and sediment yield from ungaged watersheds; storm rainfall; fluorescence and polarization of water and its contained substances; discriminating between sediment and chlorophyll in water; role of barrier island dynamics in coastal zone processes; the relationship between remotely measured surface roughness and hydraulic roughness of land surfaces and stream networks; and modeling the runoff process.

Ragan, R.↗