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At least 397 records · Page 22

General purpose free floating platform for KC-135 flight experimentation

The Controlled Ecological Life Support Systems (CELSS) program is evaluating higher plants as a means of providing life support functions aboard space craft. These plant systems will be capable of regenerating air and water while meeting some of the food requirements of the crew. In order to grow plants in space, a series of systems are required to provide the necessary plant support functions. Some of the systems required for CELSS experiments are such that is is likely that existing technologies will require refinement, or novel technologies will need to be developed. To evaluate and test these technologies, a series of KC-135 precursor flights are being proposed. A general purpose free floating experiment platform is being developed to allow the KC-135 flights to be used to their fullest. This paper will outline the basic design for the CELSS Free Floating Test Bed (FFTB), and the requirements for the individual subsystems. Several preliminary experiments suitable for the free floater will also be discussed.

Borchers, Bruce A.↗

Measurement of In-Flight Aircraft Emissions

Aircraft engine emission and their chemical and physical evolution can be measured in flight using high resolution infrared spectroscopy. The Airborne Emission Spectrometer (AES), designed for remote measure- ments of atmosphere emissions from an airborne platform, is an ideal tool for the evaluation of aircraft emissions and their evolution. Capabilities of AES will be discussed. Ground data will be given.

Aircraft Emissions Spectrometer AES↗

First International Diagnosis Competition - DXC'09

A framework to compare and evaluate diagnosis algorithms (DAs) has been created jointly by NASA Ames Research Center and PARC. In this paper, we present the first concrete implementation of this framework as a competition called DXC 09. The goal of this competition was to evaluate and compare DAs in a common platform and to determine a winner based on diagnosis results. 12 DAs (model-based and otherwise) competed in this first year of the competition in 3 tracks that included industrial and synthetic systems. Specifically, the participants provided algorithms that communicated with the run-time architecture to receive scenario data and return diagnostic results. These algorithms were run on extended scenario data sets (different from sample set) to compute a set of pre-defined metrics. A ranking scheme based on weighted metrics was used to declare winners. This paper presents the systems used in DXC 09, description of faults and data sets, a listing of participating DAs, the metrics and results computed from running the DAs, and a superficial analysis of the results.

Kurtoglu, tolga↗

XHAB 2012 Final Report Habitat Demonstration Unit Lite

The University of Maryland Space Systems Laboratory (SSL) was awarded a NASA X-Hab 2012 grant for the design and construction of a new Earth analogue habitat for habitability research. This work builds on the past ECLIPSE and X-Hab projects at the SSL, by combining these elements with a new habitat module in order to create a single research platform for habitability studies. The “Crew Habitat Evaluator for Long-duration Orbital, Near-earth, and Interplanetary Applications” (CHELONIA) will deliver a much more flexible architecture than the previously developed mock-ups, allowing facilitating faster modification of the interior layouts and available total volume. This will enable the investigators to evaluate crew assessments and task performance as a function of the interior layout, functional area allocation and total available volume. This paper documents the design of this new infrastructure, and includes the details of the manufacturing of a new habitat mock-up module and modifications to the existing elements. The paper also includes a brief discussion of possible future research goals. Initial layouts are implemented using foam-core volumetric mock-ups for internal equipment and outfitting. These low fidelity mock-ups constitute a “library” that will allow a very rapid evaluation of a multitude of layouts. CHELONIA is also suitable for higher fidelity functional mock-ups, as well as short to medium-duration mission simulations. This new facility will enable the examination of habitat layouts for both partial gravity and microgravity environments. While partial gravity systems will be easily evaluated with the habitat currently in development, microgravity subsystems will be studied by utilizing low fidelity volumetric neutral buoyancy mock-ups in order to determine if commonality in the design for these two environments is appropriate. Finally, this new facility is being integrated into the SSL Moonyard planetary surface simulation center. The Moonyard simulates a planetary surface by means of a large sandbox, and is used primarily for rover field trials and suit systems evaluation. This new facility will be a prime element in future Earth analog simulations at the University of Maryland in support of NASA exploration objectives.

Kevin Davis↗

Machine learning based noise reduction for satellite products: application to solar-induced fluorescence retrievals using simulated and real data

In the past two decades, global satellite measurements of terrestrial chlorophyll solar-induced fluorescence (SIF) have been used widely for a number of different applications related to physiology, phenology, and productivity of plants. However, SIF retrievals are inherently noisy due to the relatively small SIF spectral signature in comparison with observational noise. In this work, we examine how a spectral-based approach that employs principal component analysis along with a relatively shallow artificial neural network can be used to reduce noise and other artifacts in satellite level 2 (L2) products. We first apply the approach in a controlled environment in which radiance spectra are simulated with a full atmospheric and surface radiative transfer model for different scenarios including various SIF values that are known. Various levels of noise can be added to the simulated spectra. Resulting noisy and noise-reduced SIF retrievals are compared with the true values to assess performance. We then apply the noise reduction approach to real SIF derived from instruments flying on meteorological satellites. The results are evaluated by comparing SIF retrievals from different platforms with each other and with other independent data sets, showing enhanced capability to capture seasonal and interannual variability in SIF.

Chlorophyll fluorescence↗

NREL’s Virtual Cyber Research Platform

Watch this video to learn how NREL researchers are evaluating the interdependencies between power systems and network communication flows when cyber and physical threats to the grid occur. NREL’s cybersecurity researchers have developed an emulated, multilayer grid environment at the ESIF, where they can safely launch attacks in the virtual world on both emulated and actual physical devices throughout the facility—and evaluate how they would respond to an attack in the real world.

29 ENERGY PLANNING, POLICY, AND ECONOMY↗

Attack-resilient algorithms and testbed federation for wide-area protection and control in smart grid

Today’s energy infrastructure is undergoing a massive transformation across all generation, transmission, and distribution systems to provide reliability, efficiency, and sustainability to the power system network. During the past 10 years, there has been a remarkable enhancement in developing close-loop wide-area protection and control (WAPAC) applications, such as automatic generation control (AGC), wide-area protection scheme (WAPS), synchrophasor-based wide-area voltage control system (WAVCS), etc., in the energy management system (EMS) to provide an adequate situational awareness to control center operators during physical disturbances and natural events. The rapid digitalization, unencrypted communication, and numerous data-sharing devices have increased digital access points that have exposed the grid network to countless cyberattacks pertinent to the WAPAC cybersecurity. Given the amount of complex grid network coupled with legacy infrastructures, it is untrustworthy to completely rely on information technology (IT)-based conventional security measures to defend against evolving cyberattacks. Hence, there is a compelling need to go beyond the traditional paradigm of ‘security by obscurity’ and ‘bolt-on’ security measures, and develop a suite of innovative security solutions at multiple layers to transform the current “fault-resilient” grid into “fault and attack-resilient” grid of the future. This dissertation specifically focuses on developing application-specific attack-resilient solutions for critical WAPAC applications in the smart grid. The first part of the study, Attack-Resilient Wide-Area Protection Scheme, presents a cyber-physical attack-resilient system (CPARS) for WAPS, where two anomaly detection methods are proposed to detect multi-level cyberattacks followed by the rules-based intrusion mitigation system (RIMS) to initiate effective mitigation strategies, tailored to these attacks, to restore the normal grid operation after disturbances. The first anomaly detection component, Machine learning-based Anomaly Detection for Centralized WAPS, discusses a novel architecture and methodology for developing a machine-learning-based anomaly detection system (ADS) for the centralized wide-area protection system (CWAPS) by applying the variational mode decomposition (VMD) technique and decision tree (DT) algorithms using cyber logs and synchrophasor measurements. The second component, Multi-Agent-based Anomaly Detection for Decentralized WAPS, presents a two-level hierarchical multi-agent-based decentralized WAPS against the system-aware stealthy cyber-attacks. Finally, for the RIMS, the state transition diagram-based mitigation measures are defined based on the grid operation states and experimental testing and evaluation are presented in a cyber-physical testbed environment. The second part of the study, Attack-Resilient Wide-Area Voltage Control System, addresses the existing vulnerabilities in the wide-area voltage control system (WAVCS), presents the methodology for performing an impact analysis during data integrity attacks, and proposes a data-driven attackresilient system (DARS) by incorporating machine learning-based ADS and rules-based anomaly mitigation system (RAMS) to detect these attacks and provide necessary mitigation actions to maintain the transient voltage stability after disturbances. Finally, the third part, Networked Federation Testbed (NEFTSec) for Smart Grid Cybersecurity, focuses on developing an interconnected federated testbed through a common network like the internet, describes its conceptual architectures, and also presents its design components for experimental testing, validation, and evaluation. Further, it presents the co-simulation interface algorithm (CIA) to facilitate the geographically-dispersed real-time distributed simulation (GD-RTDS) during the cyber-physical federation. In general, this dissertation presents innovative attack-resilient solutions for WAPAC applications that are experimentally tested and evaluated using the PowerCyber testbed and NEFTSec platform to accelerate the transition of state-of-the-art research works to the real-field deployments.

24 POWER TRANSMISSION AND DISTRIBUTION↗

Mid-IR UAV-based sensing platform with deep learning to Identify and Quantify Gaseous Emission in Gas Flares

This report details the development and evaluation of a Mid-Infrared (Mid-IR) Unmanned Aerial Vehicle (UAV)-based sensing platform integrated with deep learning algorithms for the identification and quantification of gaseous emissions in gas flares. The project, spearheaded by Omega Optics, Inc., aimed to address environmental monitoring challenges by leveraging advanced photonic technologies and autonomous UAV operations. The research focused on designing, optimizing, and fabricating photonic crystal waveguides and grating couplers to enhance the sensitivity and accuracy of gas detection. A comprehensive drone-based system was developed, featuring a miniaturized sensor, GPS module, and microcontroller communication network for real-time gas concentration monitoring. The system's adaptive sampling algorithm, implemented using the Robot Operating System (ROS), enables autonomous detection and localization of gas emission sources. Preliminary results demonstrate the platform's capability to detect and monitor gas emissions with high precision, cost-effectiveness, and scalability. Future work will expand upon this foundation by introducing 3D wind model-based learning for dynamic environmental conditions and further enhancing the user interface and data processing algorithms to support broader environmental monitoring applications. Overall, this project represents a significant step forward in UAV-based environmental sensing technologies, offering robust solutions for detecting and mitigating the impacts of gaseous emissions on public health and safety.

47 OTHER INSTRUMENTATION↗

Evaluation of g seat augmentation of fixed-base/moving base simulation for transport landings under two visually imposed runway width conditions

Vertical-motion cues supplied by a g-seat to augment platform motion cues in the other five degrees of freedom were evaluated in terms of their effect on objective performance measures obtained during simulated transport landings under visual conditions. In addition to evaluating the effects of the vertical cueing, runway width and magnification effects were investigated. The g-seat was evaluated during fixed base and moving-base operations. Although performance with the g-seat only improved slightly over that with fixed-base operation, combined g-seat platform operation showed no improvement over improvement over platform-only operation. When one runway width at one magnification factor was compared with another width at a different factor, the visual results indicated that the runway width probably had no effect on pilot-vehicle performance. The new performance differences that were detected may be more readily attributed to the extant (existing throughout) increase in vertical velocity induced by the magnification factor used to change the runway width, rather than to the width itself.

Parrish, R. V.↗

Combining Simulation and Emulation Systems for Smart Grid Planning and Evaluation

Software-defined networking (SDN) enables efficient network management. As the technology matures, utilities are looking to integrate those benefits to their operations technology (OT) networks. To help the community to better understand and evaluate the effects of such integration, we develop DSSnet, a testing platform that combines a power distribution system simulator and an SDN-based network emulator for smart grid planning and evaluation. DSSnet relies on a container-based virtual time system to achieve efficient synchronization between the simulation and emulation systems. To enhance the system scalability and usability, we extend DSSnet to support a distributed controller environment. To enhance system fidelity, we extend the virtual time system to support kernel-based switches. In conclusion, we also evaluate the system performance of DSSnet and demonstrate the usability of DSSnet with a resilient demand response application case study.

24 POWER TRANSMISSION AND DISTRIBUTION↗

Employing MACS/ViBRANT as a Surrogate MARVEL Reactor for Startup Reactivity Tuning and Supervisory Control Processes

Advanced nuclear reactors are a key part of the future of nuclear energy both in the United States and globally. They offer unique benefits for various energy-demanding applications, including use in remote locations, compact size, modular manufacturing, remote monitoring, low and/or variable power rating operation, and reliance on novel technologies to enhance operational safety. To achieve economic feasibility, advanced reactors must significantly reduce their workforces in comparison with the current fleet. Achieving this reduction will occur through reducing staff workloads using technology to achieve autonomous or semi-autonomous operations, demonstrated by comprehensive testing and validation activities. These operations will require both software and hardware platforms during the design and testing phases. While simulations are useful during the design phase, their performance can significantly deviate during actual deployment on hardware. This report presents the outcomes of a collaborative technical initiative between the U.S. Department of Energy (DOE) Microreactor Program (MRP) and Advanced Sensors and Instrumentation (ASI) Program. The collaboration utilized the Microreactor Automated Control System (MACS) hardware platform to bridge the gap between theoretical reactor design and actual startup and control operations. Two key use cases were investigated: facilitating the startup testing period and demonstrating supervisory control. The first use case details the key Microreactor Applications Research Validation and Evaluation (MARVEL) reactor startup physics testing activities conducted using the MACS platform. These activities included drum worth measurements, shutdown margin assessment, temperature feedback analysis, and scram time evaluation, as well as unique testing that would apply to the MARVEL reactor to demonstrate the testing methodologies in a low-risk environment. The MACS platform, serving as a surrogate representation of the MARVEL reactor, proved instrumental in performing these tests. The exercise revealed aspects that led to optimized processes, refined hardware design, and enhanced base software capabilities. By maturing methods and technologies in this manner, the initiative promises to reduce wasted time in the actual on-site reactor deployment effort, thereby saving significant time and resources. The second use case focuses on the development and implementation of supervisory control methods aimed at managing core tilt, which can result from asymmetrical operations or manufacturing imperfections in fuel rods or reactivity control devices. A key objective was to assess and compare the use of artificial intelligence (AI) for supervisory control. The effort aimed to define the role of supervisory control to enhance performance without risking control instability. This effort explored three distinct approaches: rules-based (RB) methods, optimization techniques, and reinforcement learning (RL) algorithms. Each approach was evaluated for its ease of implementation, its usability, and its effectiveness in responding to asymmetries in neutron flux. Comparative analysis of these approaches provided valuable insights into their applicability and effectiveness, offering a robust framework for advanced reactor operations. Together, these two use cases highlight the potential of hardware test beds to help streamline the design, operation, and control of advanced nuclear reactors. This collaborative effort underscores the importance of continued innovation and experimentation in achieving the next generation of safe, reliable, and economically viable nuclear energy solutions.

22 - GENERAL STUDIES OF NUCLEAR REACTORS↗

The NOAA Satellite Observing System Architecture Study

NOAA is beginning a study, the NOAA Satellite Observing System Architecture (NSOSA) study, to plan for the future operational environmental satellite system that will follow GOES and JPSS, beginning about 2030. This is an opportunity to design a modern architecture with no pre-conceived notions regarding instruments, platforms, orbits, etc. The NSOSA study will develop and evaluate architecture alternatives to include partner and commercial alternatives that are likely to become available. The objectives will include both functional needs and strategic characteristics (e.g., flexibility, responsiveness, sustainability). Part of this study is the Space Platform Requirements Working Group (SPRWG), which is being commissioned by NESDIS. The SPRWG is charged to assess new or existing user needs and to provide relative priorities for observational needs in the context of the future architecture. SPRWG results will serve as input to the process for new foundational (Level 0 and Level 1) requirements for the next generation of NOAA satellites that follow the GOES-R, JPSS, DSCOVR, Jason-3, and COSMIC-2 missions.

Value Model↗

Evaluation of an in vitro three-dimensional HepaRG spheroid model for genotoxicity testing using the high-throughput CometChip platform

Three-dimensional (3D) culture systems are increasingly being used for genotoxicity studies due to improved cell-to-cell interactions and tissue-like structures that are limited or lacking in 2D cultures. The present study optimized a 3D culture system using metabolically competent HepaRG cells for in vitro genotoxicity testing. 3D HepaRG spheroids, formed in 96- or 384-well ultra-low attachment plates, were exposed to various concentrations of 34 test articles, including 8 direct-acting and 11 indirect-acting genotoxicants/carcinogens as well as 15 compounds that show different genotoxic responses in vitro and in vivo. DNA damage was evaluated using the high-throughput CometChip assay with concurrent cytotoxicity assessment by the ATP assay in both 2D and 3D cultures. 3D HepaRG spheroids maintained a stable phenotype for up to 30 days with higher levels of albumin secretion, cytochrome P450 gene expression, and enzyme activities compared to 2D cultures. 3D spheroids also demonstrated a higher sensitivity than 2D cultures for detecting both direct- and indirect-acting genotoxicants/carcinogens, indicating a better prediction of in vivo genotoxicity responses. When DNA damage dose-response data were quantified using PROAST software, 3D spheroids generally had lower or similar benchmark dose values compared to 2D HepaRG cells and were more comparable with primary human hepatocytes. These results demonstrate that 3D models can be adapted to the CometChip technology for high-throughput genotoxicity testing and that 3D HepaRG spheroids may be used as a reliable and pragmatic in vitro approach to better support the hazard identification and risk assessment of potential human genotoxic carcinogens.

60 APPLIED LIFE SCIENCES↗

Traffic Signal Optimization by Integrating Reinforcement Learning and Digital Twins

Machine learning (ML) methods, especially reinforcement learning (RL), have been widely considered for traffic signal optimization in intelligent transportation systems. Most of these ML methods are centralized, lacking in scalability and adaptability in large traffic networks. Further, it is challenging to train such ML models due to the lack of training platforms and/or the cost of deploying and training in a real traffic networks. This paper presents an approach for the integration of decentralized graph-based multi-agent reinforcement learning (DGMARL) with a Digital Twin (DT) to optimize traffic signals for the reduction of traffic congestion and network-wide fuel consumption related to stopping. Specifically, the DGMARL agents learn traffic state patterns and make decisions regarding traffic signal control with assistance from a Digital Twin module, which simulates and replicates the traffic behaviors of a real traffic network. The proposed approach was evaluated using PTV-Vissim [1], a microscopic traffic simulation platform. PTV-Vissim is also the simulation engine of the DT, enabling emulation and optimization of the traffic signals on the MLK Smart Corridor in Chattanooga, Tennessee. Compared to an actuated signal control baseline approach, experiment results show that Eco_PI, a developed performance measure capturing the impact of stops on fuel consumption, was reduced by 44.27% in a 24-hour and an average of 29.88% in a PM-peak-hour scenario.

Multi-Agent Reinforcement Learning, Digital Twin, ↗

An Atmospheric Science Observing System Simulation Experiment (OSSE) Environment

An atmospheric sounding mission starts with a wide range of concept designs involving measurement technologies, observing platforms, and observation scenarios. Observing system simulation experiment (OSSE) is a technical approach to evaluate the relative merits of mission and instrument concepts. At Jet Propulsion Laboratory (JPL), the OSSE team has developed an OSSE environment that allows atmospheric scientists to systematically explore a wide range of mission and instrument concepts and formulate a science traceability matrix with a quantitative science impact analysis. The OSSE environment virtually creates a multi-platform atmospheric sounding testbed (MAST) by integrating atmospheric phenomena models, forward modeling methods, and inverse modeling methods. The MAST performs OSSEs in four loosely coupled processes, observation scenario exploration, measurement quality exploration, measurement quality evaluation, and science impact analysis.

mission concepts↗

New Air-Launched Small Missile (ALSM) Flight Testbed for Hypersonic Systems

A new testbed for hypersonic flight research is proposed. Known as the Phoenix air-launched small missile (ALSM) flight testbed, it was conceived to help address the lack of quick-turnaround and cost-effective hypersonic flight research capabilities. The Phoenix ALSM testbed results from utilization of two unique and very capable flight assets: the United States Navy Phoenix AIM-54 long-range, guided air-to-air missile and the NASA Dryden F-15B testbed airplane. The U.S. Navy retirement of the Phoenix AIM-54 missiles from fleet operation has presented an excellent opportunity for converting this valuable flight asset into a new flight testbed. This cost-effective new platform will fill an existing gap in the test and evaluation of current and future hypersonic systems for flight Mach numbers ranging from 3 to 5. Preliminary studies indicate that the Phoenix missile is a highly capable platform. When launched from a high-performance airplane, the guided Phoenix missile can boost research payloads to low hypersonic Mach numbers, enabling flight research in the supersonic-to-hypersonic transitional flight envelope. Experience gained from developing and operating the Phoenix ALSM testbed will be valuable for the development and operation of future higher-performance ALSM flight testbeds as well as responsive microsatellite small-payload air-launched space boosters.

Bui, Trong T.↗

Precision and Limits of Detection for Selected Commercially Available, Low-Cost Carbon Dioxide and Methane Gas Sensors

The performance of a sensor platform for environmental or industrial monitoring is sensitive to the cost and performance of the individual sensor elements. Thus, the detection limits, accuracy, and precision of commercially available, low-cost carbon dioxide and methane gas concentration sensors were evaluated by precise measurements at known gas concentrations. Sensors were selected based on market availability, cost, power consumption, detection range, and accuracy. A specially constructed gas mixing chamber, coupled to a precision bench-top analyzer, was used to characterize each sensor during a controlled exposure to known gas concentrations. For environmental monitoring, the selected carbon dioxide sensors were characterized around 400 ppm. For methane, the sensor response was first monitored at 0 ppm, close to the typical environmental background. The selected sensors were then evaluated at gas concentrations of several thousand ppm. The determined detection limits accuracy, and precision provides a set of matrices that can be used to evaluate and select sensors for integration into a sensor platform for specific applications.

Honeycutt, Wesley T. (ORCID:0000000236814810)↗