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At least 793 records · Page 44

Flight Hardware Fabricated for Combustion Science in Space

NASA Glenn Research Center s Telescience Support Center (TSC) allows researchers on Earth to operate experiments onboard the International Space Station (ISS) and the space shuttles. NASA s continuing investment in the required software, systems, and networks provides distributed ISS ground operations that enable payload developers and scientists to monitor and control their experiments from the Glenn TSC. The quality of scientific and engineering data is enhanced while the long-term operational costs of experiments are reduced because principal investigators and engineering teams can operate their payloads from their home institutions.

OMalley, Terence F.↗

Tunable Optical Assembly with Vibration Dampening

Since their market introduction in 1995, fiber Bragg gratings (FBGs) have emerged as excellent means of measuring such parameters as strain and temperature. Distributed-grating sensing is particularly beneficial for such structural-health monitoring applications such as those of 'smart' structures or integrated vehicle health management in aerospace vehicles. Because of the variability of their output wavelengths, tunable lasers have become widely used as means of measuring FBGs. Several versions of a lightweight assembly for strain-tuning an FBG and dampening its vibrations have been constructed. The main components of such an assembly are one or more piezoelectric actuators, an optical fiber containing one or more Bragg grating(s), a Bragg-grating strain-measurement system, and a voltage source for actuation. The piezoelectric actuators are, more specifically, piezoceramic fiber composite actuators and, can be, still more specifically, of a type known in the art as macro-fiber composite (MFC) actuators. In fabrication of one version of the assembly, the optical fiber containing the Bragg grating(s) is sandwiched between the piezoelectric actuators along with an epoxy that is used to bond the optical fiber to both actuators, then the assembly is placed in a vacuum bag and kept there until the epoxy is cured. Bonding an FBG directly into an MFC actuator greatly reduces the complexity, relative to assemblies, that include piezoceramic fiber composite actuators, hinges, ferrules, and clamp blocks with setscrews. Unlike curved actuators, MFC actuators are used in a flat configuration and are less bulky. In addition, the MFC offers some vibration dampening and support for the optical fiber whereas, in a curved piezoelectric actuator assembly, the optical fiber is exposed, and there is nothing to keep the exposed portion from vibrating.

Shams, Qamar A.↗

Overview of the LADEE Ultraviolet-visible Spectrometer: Design, Performance and Planned Operations

The Lunar Atmosphere and Dust Environment Explorer (LADEE) is an orbital lunar science mission currently under development to address the goals of the 2003 National Research Council decadal survey, the Lunar Exploration Analysis Group Roadmap, and the "Scientific Context for Exploration of the Moon" (SCEM) report, and has been recommended for execution by the 2011 Planetary Missions Decadal Survey. The mission s focus is to study the pristine state of the lunar atmosphere and dust environment prior to possible lunar exploration activities by countries, including the United States, China, India, and Japan, among others. Activity on the lunar surface has the potential of altering the tenuous lunar atmosphere, but changing the type and concentration of gases in the atmosphere. Before these activities occur it is important to make measurements of the current lunar atmosphere in its unmodified state. LADEE will determine the composition of the lunar atmosphere and investigate the processes that control its distribution and variability, including sources, sinks, and surface interactions. It will monitor variations in known gases, such as sodium, potassium, argon and helium, and will search for other, as-yet-undetected gases of both lunar and extra-lunar origin. LADEE will also determine whether dust is present in the lunar exosphere, and reveal the processes that contribute to its sources and variability. Launch is planned for August, 2013.

Colaprete, A.↗

Observations of Titanium, Aluminum and Magnesium in the Lunar Exosphere by LADEE UVS

The Lunar Atmosphere and Dust Environment Explorer (LADEE) was an orbital lunar science mission designed to address the goals of the 2003 National Research Council decadal survey, the Lunar Exploration Analysis Group Roadmap, and the "Scientific Context for Exploration of the Moon" (SCEM) report, and has been recommended for execution by the 2011 Planetary Missions Decadal Survey. The LADEE mission goal was to determine the composition of the lunar atmosphere and investigate the processes that control its distribution and variability, including sources, sinks, and surface interactions. It will monitor variations in known gasses, such as sodium, potassium, argon and helium, and will search for other, as-yet-undetected gasses of both lunar and extra-lunar origin. Another goal of LADEE was to determine whether dust is present in the lunar exosphere, and reveal the processes that contribute to its sources and variability.

The Ultraviolet-Visible Spectrometer (UVS)↗

Smart Sensor Systems for Human Health and Environmental Applications

Sensors and sensor systems are central to providing improved awareness of an individual's health state and surroundings. This presentation describes efforts to develop Smart Sensor Systems for a range of health and safety applications moving towards distributed intelligence. This includes efforts to develop a human health breath monitoring system using this microsensor Smart Sensor System approach. The same core technology can be used for a range of applications related to improved human health and environmental monitoring. Other examples of human health relevant technology development will also be given.

Smart Sensors Health↗

Impact of Size Distribution Assumption on PM2.5 Simulation

Aerosol particles, especially those with diameter that is smaller than 2.5um, i.e. PM2.5, have detrimental impact on public health. As a regulated criteria air pollutant, PM2.5 is monitored by ground networks using various instruments. At the same time aerosol assimilation modeling system is developed to simulate the aerosol distribution with continuous global coverage. In this study we compared the PM2.5 simulated by NASA’s MERRA-2 modeling system with the measurements made at US Embassy sites around the globe on diurnal cycle, monthly average, and interannual variabilities. We focused the comparison in the places that are significantly impacted by the desert dust. Simulations based on both aerodynamic and geometric diameters are compared with available measurements. Aerodynamic diameter assumption shows better model-observation agreements over several dust belt stations.

Qian Tan↗

A Study of a Monitoring Program for Intermediate Depth Disposal of Low- Level Radioactive Waste - 20167

This study investigated a monitoring program for intermediate depth disposal of low-level radioactive waste. At first, it extracted monitoring targets, such as the status of cracks in the low diffusion layer after closure of the facility. Secondly, it focused on distributed optical fiber sensors which can minimize the amount of cable, and measurement positions and methods were specifically determined to propose the monitoring method. Finally, conformity to regulatory requirements was verified to clarify key points and issues to be addressed in performing monitoring. (authors)

12 MANAGEMENT OF RADIOACTIVE AND NON-RADIOACTIVE W↗

Distributed Intrusion Detection System using Semantic-based Rules for SCADA in Smart Grid

Cyber-physical system (CPS) security for the smart grid enables secure communication for the SCADA and wide-area measurement system data. Power utilities world-wide use various SCADA protocols, namely DNP3, Modbus, and IEC 61850, for the data exchanges across substation field devices, remote terminal units (RTUs), and control center applications. Adversaries may exploit compromised SCADA protocols for the reconnaissance, data exfiltration, vulnerability assessment, and injection of stealthy cyberattacks to affect power system operation. In this paper, we propose an efficient algorithm to generate robust rule sets. We integrate the rule sets into an intrusion detection system (IDS), which continuously monitors the DNP3 data traffic at a substation network and detects intrusions and anomalies in real-time. To enable CPS-aware wide-area situational awareness, we integrated the methodology into an open-source distributed-IDS (D-IDS) framework. The D-IDS facilitates central monitoring of the detected anomalies from the geographically distributed substations and to the control center. The proposed algorithm provides an optimal solution to detect network intrusions and abnormal behavior. Different types of IDS rules based on packet payload, packet flow, and time threshold are generated. Further, IDS testing and evaluation is performed with a set of rules in different sequences. The detection time is measured for different IDS rules, and the results are plotted. All the experiments are conducted at Power Cyber Lab, Iowa State University, for multiple power grid models. After successful testing and evaluation, knowledge and implementation are transferred to field deployment.

24 POWER TRANSMISSION AND DISTRIBUTION↗

Enhanced resolution particle size distributions by multiple angle photon correlation spectroscopy

Photon correlation spectroscopy (PCS) has become a method of choice for measuring submicrometer particles. It is capable of rapid, accurate measurements of mean particle size. Since the measurements are nonperturbing, it is ideal for monitoring systems undergoing dynamic changes. Despite its widespread acceptance, the information content of PCS measurements for particle size distributions is low and provides limited resolution. A method is presented whereby PCS measurements made at several scattering angles plus the angular distribution of light scattered from the particles are combined in a single simultaneous analysis to effect an enhanced resolution particle size distribution. The efficacy of the method is assessed by recovering size distributions from computer simulated data and by comparisons of conventional PCS measurements of polystyrene spheres with those made by the new method.

Bott, Steven E.↗

The CMS Magnetic Field Measuring and Monitoring Systems

This review article describes the performance of the magnetic field measuring and monitoring systems for the Compact Muon Solenoid (CMS) detector. To cross-check the magnetic flux distribution obtained with the CMS magnet model, four systems for measuring the magnetic flux density in the detector volume were used. The magnetic induction inside the 6 m diameter superconducting solenoid was measured and is currently monitored by four nuclear magnetic resonance (NMR) probes installed using special tubes outside the barrel hadron calorimeter. Two more NRM probes were installed at the faces of the tracking system. The field inside the superconducting solenoid was precisely measured in 2006 in a cylindrical volume of 3.448 m in diameter and 7 m in length using 10 three-dimensional (3D) B-sensors based on the Hall effect. These B-sensors were installed on each of the two propeller arms of an automated field-mapping machine. In addition to these measurement systems, a system for monitoring the magnetic field during the CMS detector operation has been developed. Inside the solenoid in the horizontal plane, 4 3D B-sensors were installed at the faces of the tracking detector. Twelve 3D B-sensors were installed on the surfaces of the flux-return yoke nose disks. Seventy 3D B-sensors were installed in the air gaps of the CMS magnet yoke. A specially developed flux loop technique was used for the most complex measurements of the magnetic flux density inside the steel blocks of the CMS magnet yoke. The flux loops are installed in 22 sections of the flux-return yoke blocks. The areas enclosed by these coils varied from 0.3 to 1.59 m$^{2}$ in the blocks of the barrel wheels and from 0.5 to 1.12 m$^{2}$ in the blocks of the yoke endcap disks. The development of these systems and the results of the magnetic flux density measurements across the CMS magnet are presented and discussed in this review article.

46 INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AND ↗

High-resolution modeling of indoor radon exposure with uncertainty quantification in Utah

Indoor radon accounts for 37% of population-level exposure to ionizing radiation in the United States. However, radon metrics are typically reported at coarse spatial scales, potentially obscuring meaningful local variation. We developed a high-resolution modeling framework to estimate indoor radon concentrations across Utah while explicitly quantifying predictive uncertainty. A total of 19,497 residential radon measurements collected between 2006 and 2017 were combined with environmental and housing characteristics and analyzed using a geospatial neural network that accommodates spatial dependence and nonlinear associations. Predictions were generated on a uniform hexagonal grid at 0.73 km2 resolution (H3 level 8). Out-of-sample predictions aggregated to the H3 level 8 grid showed good agreement with observed concentrations (Pearson r=0.64), while household-level predictions exhibited more moderate agreement (r=0.45). The model produced well-calibrated uncertainty estimates, with 24.1% of held-out observations exceeding the predicted 75th-percentile threshold. Maps of predicted radon concentrations and the probability of exceeding the U.S. EPA action level of 148 Bq/m3 (4 pCi/L) revealed substantial fine-scale spatial heterogeneity that was not apparent in conventional coarse-resolution summaries, with greater local variability observed in densely monitored urban counties than in sparsely sampled regions. High-resolution radon models that explicitly quantify uncertainty provide a useful framework for characterizing the spatial distribution of indoor radon and identifying areas of elevated exceedance risk. These findings highlight the value of fine-scale monitoring data and uncertainty-aware modeling approaches for radon exposure assessment, environmental risk characterization, and radon-related health research.

Wu, Yunhan [ORNL] (ORCID:0000000178842994)↗

Monitoring and control requirement definition study for Dispersed Storage and Generation (DSG), volume 1

Twenty-four functional requirements were prepared under six categories and serve to indicate how to integrate dispersed storage generation (DSG) systems with the distribution and other portions of the electric utility system. Results indicate that there are no fundamental technical obstacles to prevent the connection of dispersed storage and generation to the distribution system. However, a communication system of some sophistication is required to integrate the distribution system and the dispersed generation sources for effective control. The large-size span of generators from 10 KW to 30 MW means that a variety of remote monitoring and control may be required. Increased effort is required to develop demonstration equipment to perform the DSG monitoring and control functions and to acquire experience with this equipment in the utility distribution environment.

Source record↗

Quantum Key Distribution for Critical Infrastructures: Towards Cyber-Physical Security for Hydropower and Dams

Hydropower facilities are often remotely monitored or controlled from a centralized remote control room. Additionally, major component manufacturers monitor the performance of installed components, increasingly via public communication infrastructures. While these communications enable efficiencies and increased reliability, they also expand the cyber-attack surface. Communications may use the internet to remote control a facility’s control systems, or it may involve sending control commands over a network from a control room to a machine. The content could be encrypted and decrypted using a public key to protect the communicated information. These cryptographic encoding and decoding schemes become vulnerable as more advances are made in computer technologies, such as quantum computing. In contrast, quantum key distribution (QKD) and other quantum cryptographic protocols are not based upon a computational problem, and offer an alternative to symmetric cryptography in some scenarios. Although the underlying mechanism of quantum cryptogrpahic protocols such as QKD ensure that any attempt by an adversary to observe the quantum part of the protocol will result in a detectable signature as an increased error rate, potentially even preventing key generation, it serves as a warning for further investigation. In QKD, when the error rate is low enough and enough photons have been detected, a shared private key can be generated known only to the sender and receiver. We describe how this novel technology and its several modalities could benefit the critical infrastructures of dams or hydropower facilities. The presented discussions may be viewed as a precursor to a quantum cybersecurity roadmap for the identification of relevant threats and mitigation.

97 MATHEMATICS AND COMPUTING↗

Enhancing Human Health Using Space Imagery: Summary of Research

The International Space University (ISU) 2002 Summer Session was conducted in Pomona, California, June 29-August 30, 2002. Ninety-nine professionals and students from thirty-one countries attended the Summer Session. More than half of these students participated in the Student Research Design Project entitled, "HI-STAR: Health Improvements through Space Technologies and Resources." ISU's interdisciplinary Student Research Design Projects are intended to have great educational value for the participants and, at the same time, to result in a product that will be useful to the field. The HI-STAR project was a success on both counts. The mission of the ISU students' effort on HI-STAR was to develop and promote a global strategy to help combat malaria using space technology. Like the tiny yet powerful mosquito, HI-STAR is a small program that aspires to make a difference. Timely detection of malaria danger zones is essential to help health authorities and policy makers make decisions about how to manage limited resources for combating malaria. In 2001, the technical support network for prevention and control of malaria epidemics published a study called "Malaria Early Warning Systems: Concepts, Indicators and Partners." This study, funded by Roll Back Malaria, a World Health Organization initiative, offered a framework for a monitoring and early warning system. HI-STAR seeks to build on this proposal and enhance the space elements of the suggested framework. Malaria disease dynamics and distributions are related to environmental variables. From space, environmental conditions that support the growth of mosquito populations can be monitored, Malaria-specific information can be gathered from satellite-borne remote sensing instruments and ground-based sensors. This information can be integrated via geographic information systems (GIS) into a Malaria Information System (MIS) that can provide assessment analyses and risk maps as output. HI-STAR defines and suggests the development of an active MIS as a low-cost tool to help organizations plan their efforts to fight malaria.

Finarelli, Margaret G.↗

Ambient field seismology in critical zone hydrological sciences

Passive ambient noise monitoring is an emerging tool in environmental seismology, leveraging the ambient seismic field to assess temporal variations in shallow subsurface properties. This review focuses on the potential and challenges of using scattered coda waves from noise correlation functions to monitor critical zone dynamics. The sensitivity of seismic velocities to various environmental factors, including precipitation, snowmelt, atmospheric pressure, and groundwater fluctuations, underscores the method’s versatility. While coda waves excel in detecting subtle changes due to their scattered nature, ballistic waves provide higher spatial resolution, albeit with challenges in source stability. Advances in seismic sensing, including distributed acoustic sensing and low-cost geophone networks, have enabled high-resolution monitoring of hydrological processes, subsurface deformation, and seismic hazards. Integrating seismic data with hydrological models provides insights into water storage, pore pressure changes, and soil moisture dynamics. However, limitations in spatial resolution, calibration with ground truth data, and coupled effects between environmental factors remain key challenges. This review emphasizes the importance of interdisciplinary approaches in refining methodologies, enhancing sensor deployments, and addressing data gaps. Passive seismic monitoring offers opportunities to understand critical zone processes and their broader impacts on seismic hazards and environmental sustainability.

58 GEOSCIENCES↗

The Cryosphere/Ocean Distributed Acoustic Sensing (CODAS) Experiment

Distributed acoustic sensing (DAS) has a demonstrated potential for wide-scale and continuous in situ monitoring of near-surface environmental and anthropogenic processes. DAS is attractive for development as a multi-geophysical observatory due to the prevalence of existing fiber infrastructure in regions with environmental, cultural, or strategic significance. To evaluate the efficacy of this technology for monitoring of polar environmental processes, we collected DAS data from a 37-km long section of seafloor telecommunications fiber located on the continental shelf of the Beaufort Sea, Alaska. This experiment spanned eight, one-week, seasonally-distributed periods across two years. This was the first ever deployment of seafloor DAS beneath sea ice, and the first deployment in any marine environment to span multiple seasons. We recorded a variety of environmental and anthropogenic signals with demonstrable utility for the study of sea ice dynamics and tracking of ocean vessels and ice-traversing vehicles.

54 ENVIRONMENTAL SCIENCES↗

AI-assisted detector design for the EIC (AID(2)E)

Artificial Intelligence is poised to transform the design of complex, large-scale detectors like ePIC at the future Electron Ion Collider. Featuring a central detector with additional detecting systems in the far forward and far backward regions, the ePIC experiment incorporates numerous design parameters and objectives, including performance, physics reach, and cost, constrained by mechanical and geometric limits. This project aims to develop a scalable, distributed AI-assisted detector design for the EIC (AID(2)E), employing state-of-the-art multiobjective optimization to tackle complex designs. Supported by the ePIC software stack and using G EANT 4 simulations, our approach benefits from transparent parameterization and advanced AI features. The workflow leverages the PanDA and iDDS systems, used in major experiments such as ATLAS at CERN LHC, the Rubin Observatory, and sPHENIX at RHIC, to manage the compute intensive demands of ePIC detector simulations. Tailored enhancements to the PanDA system focus on usability, scalability, automation, and monitoring. Ultimately, this project aims to establish a robust design capability, apply a distributed AI-assisted workflow to the ePIC detector, and extend its applications to the design of the second detector (Detector-2) in the EIC, as well as to calibration and alignment tasks. Additionally, we are developing advanced data science tools to efficiently navigate the complex, multidimensional trade-offs identified through this optimization process.

97 MATHEMATICS AND COMPUTING↗

e RPCA : Robust Principal Component Analysis for Exponential Family Distributions

Abstract Robust principal component analysis (RPCA) is a widely used method for recovering low‐rank structure from data matrices corrupted by significant and sparse outliers. These corruptions may arise from occlusions, malicious tampering, or other causes for anomalies, and the joint identification of such corruptions with low‐rank background is critical for process monitoring and diagnosis. However, existing RPCA methods and their extensions largely do not account for the underlying probabilistic distribution for the data matrices, which in many applications are known and can be highly non‐Gaussian. We thus propose a new method called RPCA for exponential family distributions (), which can perform the desired decomposition into low‐rank and sparse matrices when such a distribution falls within the exponential family. We present a novel alternating direction method of multiplier optimization algorithm for efficient decomposition, under either its natural or canonical parametrization. The effectiveness of is then demonstrated in two applications: the first for steel sheet defect detection and the second for crime activity monitoring in the Atlanta metropolitan area.

Zheng, Xiaojun↗