Engineering Papers⌕ Search

SEARCH · Engineering Papers

Results for “IEEE”

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.

Quote a phrase for an exact phrase match. Source license links do not imply unrestricted reuse.

At least 1,549 records · Page 86

TSIS-1 Pointing System Performance after 5 Years on ISS

The Total and Spectral Solar Irradiance Sensor-1 (TSIS-1) was installed on the ISS in December 2017, completed its prime 5-year mission in 2023, and is now in extended operations. Within the first year of operations, the paper titled, “Challenges and Solutions for Precision Solar Pointing on the ISS for the TSIS Instrument” was presented at the 2019 IEEE Aerospace Conference. This paper described challenges associated with ISS jitter and structural obscuration along with on-orbit measurements of these phenomenon and how TSIS-1 initially performed in their presence. Since the paper was presented in 2019, TSIS-1 has continued to operate with much success. This paper will provide a 5-year update on the performance of the TSIS-1 pointing system, including additional measurements of ISS base motion jitter, updated ISS obscuration information, data trends that showed slight increases in azimuth motor torque and pointing errors, and a pointing anomaly due to contamination on one of the pointing system sun sensors. These results may help other payload developers better understand the ISS environment and long-term mechanism performance.

Patrick Brown↗

Using Mesh Networking for A Dynamic Lunar Internet of Things (Liot)

The purpose of this project is to evaluate the feasibility of an IEEE 802.11 mesh protocol for lunar surface computing. This standard for wireless networking boosts speed, dependability and range of wireless transmissions. The concept is to integrate sensors (such as deployed science instruments) or Astronaut tools (such as a handheld spectrometer) that communicate with a node on a common cell. The nodes can extend the range of the cell and can dynamically reconfigure the data routing in case of another node failure. All of the data in a cell pass through a modem that communicates with a distant base station across a 4G link. The application of mesh networking to a potential lunar surface network increases robustness and fault tolerance over a traditional single-point modem system. By demonstrating the basic capability of a mesh network, the student team has learned about issues with power, distance, thermal, dust, radiation, data processing, and communication problems applicable to the lunar surface. This knowledge can feed into future NASA requirements to improve the capability of a LunaNET implementation for the Artemis program. This project follows 10 years of successful collaboration between NASA ARES, Texas Space, Technology, Applications and Research (T STAR) and Texas A&M University in a Public, Private, Academic (PPA) Partnership. NASA funds T STAR to mentor undergraduate Capstone teams in the College of Engineering Department to design, built, and test prototypes meeting NASA requirements. TAMU faculty lead the student teams in their academic class, and NASA Subject Matter Experts (SMEs) provide T STAR and students insight on requirements evolution, prior design projects, and future development goals.

Lunar Mesh Networking↗

NASA Earth Science Technology Office (ESTO) Advanced Information Systems Technology (AIST) Program: Earth Systems Digital Twins (ESDT) Standards for Interoperable Digital Twins Workshop Presentations

On September 18, 2023, NASA Earth Science Technology Office (ESTO) Advanced Information Systems Technology (AIST) Program conducted a mini-workshop that brought together seven experts to survey and discuss "Standards for Interoperable Digital Twins". Since three years, the AIST Program has been developing technologies and prototypes for Earth System Digital Twins (ESDT). During those developments and after the ESDT Workshop held in October 2022, it became clear that standard for ESDT interoperability were needed and should be defined as soon as possible. To address this challenge, the AIST program will survey ongoing development for Digital Twins standards in various domains and the September 18, 2023 Workshop represented the first step towards this understanding. Speakers during this event included: Michael Grieves (Digital Twin Institute), Siri Jodha Singh Khalsa (IEEE GRSS Standards), Trent Tinker (OGC), Ryan Berkheimer (NOAA), John Stone (NVIDIA), Thomas Geenen (ECMWF-DestinE) and Arne Berre (SINTEF-Iliad DTO and EDITO). This presentation regroups all the speakers' presentations.

Earth Science Remote Sensing; Information Systems↗

Standards for Interoperable Digital Twins

On September 18, 2023, NASA Earth Science Technology Office (ESTO) Advanced Information Systems Technology (AIST) Program conducted a mini-workshop that brought together seven experts to survey and discuss "Standards for Interoperable Digital Twins". Since three years, the AIST Program has been developing technologies and prototypes for Earth System Digital Twins (ESDT). During those developments and after the ESDT Workshop held in October 2022, it became clear that standard for ESDT interoperability were needed and should be defined as soon as possible. To address this challenge, the AIST program will survey ongoing development for Digital Twins standards in various domains and the September 18, 2023 Workshop represented the first step towards this understanding. Speakers during this event included: Michael Grieves (Digital Twin Institute), Siri Jodha Singh Khalsa (IEEE GRSS Standards), Trent Tinker (OGC), Ryan Berkheimer (NOAA), John Stone (NVIDIA), Thomas Geenen (ECMWF-DestinE) and Arne Berre (SINTEF-Iliad DTO and EDITO). This movie represents the recording of this event.

Earth Science Remote Sensing↗

Seasonal Surface Spectral Emissivity Derived From MODIS Data

Surface emissivity is essential for many remote-sensing applications including the retrieval of surface skin temperature from satellite-based infrared measurements, the determination of cloud detection thresholds, and the estimation of the surface longwave radiation emission, an important component of the energy budget of the surface-atmosphere interface. The CERES (Clouds and the Earth’s Radiant Energy System) Project is measuring broadband shortwave and longwave radiances and deriving cloud properties from the MODIS on Terra and Aqua and from the VIIRS on NOAA-19 and NOAA-20 orbiters to produce combined global radiation and cloud property data sets. Zhou et al. (IEEE Trans. Geosci. Remote Sens., 49, 2011) used Infrared Atmospheric Sounding Interferometer (IASI) data to create a high spectral resolution surface emissivity atlas for remote sensing and modeling applications. The IASI measures spectral radiances between 3.62 and 15.5 μm. The VIIRS I4 channel width is from 3.55 to 3.93 μm, while MODIS Band 20 is from 3.66 to 3.84 m. Comparisons of top-of-atmosphere (TOA) radiance calculations with MODIS and VIIRS observations for these bands relative to bands in the mid-infrared suggest that the IASI emissivity atlas near 3.7 µm may not be suitable for CERES cloud retrievals. In this paper, the IASI emissivities for the VIIRS and MODIS bands centered near 11m are used to derive surface skin temperature from nighttime MODIS/VIIRS data. The Goddard Earth Observing System for Instrument Teams (GEOS-IT) numerical weather analyses provide temperature and water vapor profiles fused to correct the observed radiances for atmospheric absorption and emission. Global seasonal emissivity maps are then derived for the VIIRS and MODIS 3.7-m bands that are consistent with the derived skin temperatures and the observed TOA radiances. These seasonal climatology maps are validated and will be used in CERES Edition 5 and other CERES-related cloud retrieval algorithms to provide improved clear-sky radiances and derived cloud properties.

Surface Emissivity↗

Validation of a Probabilistic Continuity Assessment Method for Earth Observation Portfolios

With the increased reliance on spaceborne Earth observation data among the Earth science community and other end users, it is important that efforts are made to promote data continuity for a range of parameters of interest. Continuity gaps may occur between missions measuring like parameters due to mission development delays or early termination and introduce the potential of increased uncertainty for retrieved parameters. To inform portfolio-level decisions for Earth observing missions, Ivanco et al. developed a method that enables the assessment of the probability of continuity gaps for multi-mission architectures and provides a framework to assess this probability in the context of multiple scenarios that represent possible future states of the architecture [Ivanco et al., “A Scenario-Based Approach to Assess Continuity Gaps in Earth Observations,” IEEE Aerospace Conf., 2024]. While this method was previously applied to assess continuity gaps for a specific multi-mission architecture, it had not yet been validated with historical data. This paper outlines the process of validating the probabilistic gap assessment method by utilizing data obtained from past NASA Earth Science mission formulation documents and provides a discussion of the results and takeaways from the validation. Future areas of improvement pertaining to both the modeling and simulation methodologies and underlying assumptions are identified and discussed.

Katharine Burn↗

Seasonal Surface Spectral Emissivity Derived from VIIRS Data

Surface emissivity is essential for many remote-sensing applications including the retrieval of surface skin temperature from satellite-based infrared measurements, the determination of cloud detection thresholds, and the estimation of the surface longwave radiation emission, an important component of the energy budget of the surface-atmosphere interface. The CERES (Clouds and the Earth’s Radiant Energy System) Project is measuring broadband shortwave and longwave radiances and deriving cloud properties from the MODIS on Terra and Aqua and from the VIIRS on NOAA-19 and NOAA-20 orbiters to produce combined global radiation and cloud property data sets. Zhou et al. (IEEE Trans. Geosci. Remote Sens., 49, 2011) used Infrared Atmospheric Sounding Interferometer (IASI) data to create a high spectral resolution surface emissivity atlas for remote sensing and modeling applications. The IASI measures spectral radiances between 3.62 and 15.5 µm. The VIIRS I4 channel width is from 3.55 to 3.93 µm, while MODIS Band 20 is from 3.66 to 3.84 µm. Comparisons of top-of-atmosphere (TOA) radiance calculations with MODIS and VIIRS observations for these bands suggest that the IASI emissivity atlas near 3.7 µm may not be suitable for CERES cloud retrievals. In this paper, the IASI emissivities for the VIIRS and MODIS bands centered near 11µm are used to derive surface skin temperature from nighttime MODIS/VIIRS data. The Goddard Earth Observing System for Instrument Teams (GEOS-IT) numerical weather analyses provide temperature and water vapor profiles fused to correct the observed radiances for atmospheric absorption and emission. Global seasonal emissivity maps are then derived for the VIIRS and MODIS 3.7µm bands that are consistent with the derived skin temperatures and the observed TOA radiances. These seasonal climatology maps will be validated and used in CERES Edition 5 and other CERES-related cloud retrieval algorithms to provide improved clear-sky radiances and derived cloud properties.

Surface Emissivity↗

Digital Lunar Exploration Sites (DLES) Terrain Crafting

Humans will soon be returning to the surface of the Moon with NASA’s Artemis program. The Artemis program is an international collaboration that will consist of a complex series of space systems and missions to explore the lunar surface and pave the way for the future exploration of Mars. NASA and its partners rely heavily on simulation for lighting and navigation studies as well as training astronauts, flight controllers, and mission support staff. The NASA Exploration Systems Simulations (NExSyS) team in the Simulation and Graphics Branch (ER7) in the Engineering Directorate at NASA’s Johnson Space Center has built up many simulation products to support this effort, one of which is the Digital Lunar Exploration Sites (DLES). DLES is a collection of products used to simulate and render the lunar surface in a digital environment. We discussed and presented an overview of the DLES products at the 2022 IEEE Aerospace Conference in Big Sky, MT with a paper titled "Digital Lunar Exploration Sites". This “DLES Terrain Crafting” paper will expand on the information previously provided in “DLES” paper and dive deeper into the details of the terrain crafting process and the toolsets used to support this task. The best digital data currently available of the lunar surface is provided by the Lunar Reconnaissance Orbiter (LRO). Its Lunar Orbiter Laser Altimeter (LOLA) achieves an impressive resolution of 5m per pixel at the Lunar South Pole (LSP) and can generate datasets covering a large continuous region near the LSP. There are a few additional methods, such as Shape from Shading which can infer higher resolution data (up to 1m per pixel) from the LRO Narrow Angle Camera (NAC) images. However, surface-based simulations require higher-resolution data, and this paper will discuss the process of enhancing the terrain to meet that need. The process begins with capturing statistical data of craters in the regions of interest using images provided by the LRO NAC. This data is then used to scatter artificial features which are not captured in the truth data, resulting in an enhanced DEM with a much higher resolution of 20cm per pixel. Many tools were built up to assist in the creation of these artificial Digital Elevation Models (DEM), which this paper will discuss in detail. DEMs themselves are a very powerful representation of a planetary surface, and many operations and tools can utilize the data they contain. This paper includes a description of the rendering of the lunar surface in a graphics engine, generation of contact patches to simulate tire to ground interaction, and ray tracing utilities to model Line of Sight (LOS) interactions with the terrain. This paper will also explore some new tool sets currently under development which aim to utilize Machine Learning (ML) to assist in the identification of craters from LRO NAC imagery. While this is not a novel idea, the NExSyS team is developing a unique approach which may result in more robust identification of crater characteristics.

Artemis↗

From Blood Platelets Classification to Earth System Digital Twins: A Career in Computer Vision

IEEE SIgnal Processing Society (SPS) and Women in Signal Processing (WiSP) Webinar (https://signalprocessingsociety.org/blog/webinar-wisp-blood-platelets-classification-earth-system-digital-twins-career-computer-vision): Join us for an interactive session with Dr. Jacqueline Le Moigne, Manager of the NASA Science Mission Directorate Earth Science Technology Office’s Advanced Information Systems Technology Program. In this webinar, Dr. Le Moigne will share her journey through academia, the private sector, and her pivotal roles at NASA, emphasizing her work in signal processing, computer vision, and related technologies. The webinar will conclude with an interactive Q&A session, providing attendees the opportunity to engage directly with Dr. Le Moigne about her experiences and insights. Dr. Jacqueline Le Moigne manages NASA's Advanced Information Systems Technology Program, focusing on novel technologies that support Earth Science missions. She previously held roles at NASA Goddard, including Assistant Chief for Technology, and has worked on NASA's Space Technology Research Grants Program and Technology Roadmaps. Before NASA, she was a Research Scientist at the University of Maryland's Computer Vision Laboratory and also gained experience in the private sector. Jacqueline earned her Ph.D. in Computer Science from the University Pierre and Marie Curie in Paris. Her research interests include Image Registration, Computer Vision, Artificial Intelligence, Autonomous Systems, Distributed Spacecraft Missions (DSM), and Earth System Digital Twins (ESDT), as well as high-performance and onboard computing. She has authored over 180 publications, including books and patents, and has received multiple awards, including the NASA Exceptional Service Medal and the Goddard Information Science and Technology Award in 2012.

Computer Vision; Image Processing; Earth Science R↗

Evaluating Lunar Water Processing System Model Configurations for Small Scale Oxygen and Hydrogen Production Within JAXA'S ISRU Technology

Introduction: In-Situ Resource Utilization (ISRU) refers to novel methods of extracting and processing local resources for use in life support and propulsion systems, reducing or eliminating the required consumables to be transferred from Earth. Current estimates of water-ice availability embedded in regolith within the Moon’s permanently shadowed regions (PSR’s) range between 1-5% by weight. However, the composition and characteristics of the “wet” regolith is unknown. Alternate ISRU excavation techniques and Concept of Operations (ConOps) must be explored to optimize surface system operations based on these factors. To assess the feasibility of different ISRU subsystem technologies and compare system architecture configurations, an interchangeable system model was generated to incorporate technologies spanning excavation of raw materials to storage of products and determine optimal arrangement of total system processing needs. Total Mass, Volume, and Power (M/V/P) requirements were computed for 168 design iterations of this water processing plant. System Model: In FY24, the System Engineering and Integration (SE&I) ISRU Modeling and Analysis (SIMA) team developed a lunar water processing system model using the Mission Analysis and Integration Tool (MAIT) to estimate the M/V/P for ISRU subsystems operating under a wide range of Hydrogen (H2) and Oxygen (O2) production targets for the Space Technology Mission Directorate (STMD) [1]. Based on Japan Aerospace Exploration Agency’s (JAXA) surface operational requirements, this system architecture was modified to include the ability to excavate consolidated icy regolith (versus granular ice excavation using Kennedy Space Center’s (KSC) ISRU Pilot Excavator, IPEx) and explore the feasibility of processing the lunar water both inside and outside of the PSR. For the consolidated icy regolith case study, excavation was performed via a mobility transport chassis outfitted with The Regolith Ice Drill for Exploring New Terrain (TRIDENT) for drilling [2] and the Cold Operable Lunar Deployable Arm (COLDArm) [3] for regolith transfer. The system model determines the required rover and payload. M/V/P to handle the required regolith processing rates. The regolith is then sorted and heated to sublimate the ice (via an auger dryer). The exiting high temperature, low pressure vapor is cleaned of volatiles (via cold trap) and electrolyzed to produce H2 and O2. These products are then dried, liquified with 20 K and 90 K cryocoolers (for H2 and O2, respectively), and stored in cylindrical tanks. Study Goals: Due to the different ConOps options of regolith transport to the ridge for processing versus processing it directly inside the PSR, as well as the unknown regolith/water-ice composition, new excavation techniques and their power configurations are being evaluated within a ISRU system architecture for production targets less than NASA’s pilot plant (1 mT). This analysis investigates the feasibility of numerous excavation techniques, power architectures, and logistical operations and determines an optimal system configuration with regards to M/V/P. It aims to investigate which parameters, both locally and globally, have the greatest effect on each subsystem within the plant. This can be used to identify the most critical components of the plant, and guide future decisions on allocating funding for research and development. The results from this study may provide subsystem developers with appropriate interfaces with excavation subsystems and downstream processes, and assessing the overall feasibility of each excavation technique, power architecture, and logistical timeframe. References: [1] Carlson, A. et. al. (2024) ICES. [2] Zacny, K., et. al. (2024) “ASCE Earth and Space”. [3] McCormick, R., et. Al. (2024) IEEE Xplore.

ISRU↗

The Genesis Non-flight Implant Sample Archive

Introduction: For the past 20 years the Genesis science community has been analyzing solar wind captured in sample collectors now curated at Johnson Space Center (JSC). Non-flown flight like collector materials (non-flight) considered reference material was always allocated by the JSC Genesis team for testing experimental procedures. However, to expedite Genesis science, distribution of non-flown reference materials were also provided by, D. S. Burnett (Genesis PI, Caltech) and A. J. G. Jurewicz (ASU) who were funded to aid all Genesis PIs by providing engineering test materials archived at Caltech pre-flight as well as ion implants into these materials [1]. Implanted materials (non-flight reference, flight-like semiconductor materials, and NIST SRM glass) received from the Caltech collection during a pilot project are being used to develop an accession procedure for the purpose of making these materials available to researchers in the future. These implant samples are important because they can be utilized as measurement standards [2]. This is a work in progress and this work reports progress in documentation and imaging. The pilot program received 63 implanted reference materials with known implanted ions. Genesis Non-Flight Database: The existing non-flight material database was modified to allow for the description of implant sessions and to allow correlation of the implant information to individual specimens. An implant session has three main components: a known ion, a known dose (ion/cm2), and a known energy (keV). Procedure: Laboratory Procedure. Upon receiving non-flight analytical standards (independently calibrated implants), or implant samples (nominally calibrated implants), they will be imaged in their current containers to capture any information written before being brought into the Genesis Sample Laboratory. Documentation is provided by the donor and used for correlating the data between the implant sessions and implant samples. This information is not verified by Genesis Curation. The microscope used to image samples in the laboratory has an automated stage with a stainless-steel plate to hold samples and a camera that utilizes the software Surveyor to take photomosaic images of the implant samples. The camera attached to the microscope is a QICAM High Performance IEEE 1394 FireWire Digital CCD Camera. This setup, shown in Fig. 1, allows for photomosaics of small-scale samples with a 10x objective or 25x objective. Examples of images taken with this microscope setup are shown in Fig.2 and Fig. 3. After imaging, samples get stored in a clean fluoroware container or polypropylene vial depending on sample size for long term storage. Database Procedure. The Genesis Non-Flight Database currently allows for the addition of implant sessions. The required fields for adding an implant session are the implant session ion, the implant session dose, and the implant session energy. There are also fields for the date and vendor of the sessions as well as a field for if the session was calibrated or not. Once an implant session has been inserted into the database, additional documentation from the session can be attached. The database will automatically assign an Implant Session Number. After inserting an implant session, the implanted samples can be inserted. The fields required for an implant sample are the material of the sample and the size of the sample. The Generic name for the implant sample with be automatically generated by the database once it has been inserted. Implant sample numbers begin with 3X to distinguish from flown Genesis sample numbers. There are also fields for processors to add the location (room, cabinet, tray) and container type (fluoroware, polypropylene vial). Once an implant session and an associated sample(s) have been inserted into the database the sample can be then tied to all associated implant sessions. An implant sample can be tied to multiple implant sessions. Future work: For curation, future work consists of creating an online catalogue for implant samples as well as updating the database with more samples as we receive them. For the scientific community these implant samples have many potential uses. For Genesis research, they are directly applicable for testing and, in some cases, as analytical standards. For non-Genesis research, implants (especially calibrated implants) could be used for calibrating other, unique planetary materials [1].

C D Calva↗

PMU Data Integrity Evaluation through Analytics on a Virtual Test-Bed

Power systems are rapidly becoming populated by phasor measurement units (PMUs) in ever increasing numbers. PMUs are critical components of today s energy management systems, designed to enable near real-time wide area monitoring and control of the electric power system. They are able to measure highly accurate bus voltage phasors as well as branch current phasors incident to the buses at which PMUs are equipped. Synchrophasor data is used for applications varying from state estimation, islanding control, identifying outages, voltage stability detection and correction, disturbance recording, and others. However, PMU-measured readings may suffer from errors due to meter biases or drifts, incorrect configurations, or even cyber-attacks. Furthermore, the testing of early PMUs showed a large disparity between the reported values from PMUs provided by different manufacturers, particularly when frequency was off-nominal, during dynamic events, and when harmonic/inter-harmonic content was present. Detection and identification of PMU gross measurement errors are thus crucial in maintaining highly accurate phasor readings throughout the system. In this paper, we present our work in conducting analytics to determine the trustworthiness and worth of the PMU readings collected across an electric network system. By implementing the IEEE 118 bus test case on a virtual test bed (VTB) , we are able to emulate PMU readings (bus voltage and branch current phasors in addition to bus frequencies) under normal and abnormal conditions using (virtual) PMU sensors deployed across major substations in the network. We emulate a variety of failures such as bus, line, transformer, generator, and/or load failures. Data analytics on the voltage phase angles and frequencies collected from the PMUs show that specious (or compromised) PMU device(s) can be identified through abnormal behaviour by comparing the trend of its frequency and phase angle reading with the ensemble of all other PMU readings in the network. If the reading trend of a particular PMU deviates from the weighted average of the reading trends of other PMUs at nearby substations, then it is likely that the PMU is malfunctioning. We assign a weight to each PMU denoting how electric-topology-wise close it is from where the PMU under consideration is located. The closer a PMU is, the higher the weight it has. To compute the closeness between two nodes in the power network, we employ a form of the resistance distance metric. It computes the electrical distance by taking into consideration the underlying topology as well as the physical laws that govern the electrical connections or flows between the network components. The detection accuracy of erroneous PMUs should be improved by employing this metric. We present results to validate the proposed approach. We also discuss the effectiveness of using an end-to-end VTB approach that allows us to investigate different types of failures and their responses as seen by the ensemble of PMUs. The collected data on certain types of events may be amenable to certain types of analysis (e.g., alerting for sudden changes can be done on a small window of data) and hence determine the data analytics architectures is required to evaluate the streaming PMU data.

and data analytics architecture.↗

A New Linearization Method of Unbalanced Electrical Distribution Networks

Abstract--- With increasing penetration of distributed generation in the distribution networks (DN), the secure and optimal operation of DN has become an important concern. As DN control and operation strategies are mostly based on the linearized sensitivity coefficients between controlled variables (e.g., node voltages, line currents, power loss) and control variables (e.g., power injections, transformer tap positions), efficient and precise calculation of these sensitivity coefficients, i.e. linearization of DN, is of fundamental importance. In this paper, the derivation of the node voltages and power loss as functions of the nodal power injections and transformers' tap-changers positions is presented, and then solved by a Gauss-Seidel method. Compared to other approaches presented in the literature, the proposed method takes into account different load characteristics (e.g., constant PQ, constant impedance, constant current and any combination of above) of a generic multi-phase unbalanced DN and improves the accuracy of linearization. Numerical simulations on both IEEE 13 and 34 nodes test feeders show the efficiency and accuracy of the proposed method.

linearization↗

Distribution System Voltage Regulation by Distributed Energy Resources

This paper proposes a control method to regulate voltages in 3 phase unbalanced electrical distribution systems. A constrained optimization problem to minimize voltage deviations and maximize distributed energy resource (DER) active power output is solved by harmony search algorithm. IEEE 13 Bus Distribution Test System was modified to test three different cases: a) only voltage regulator controlled system b) only DER controlled system and c) both voltage regulator and DER controlled system. The simulation results show that systems with both voltage regulators and DER control provide better voltage profile.

Distributed energy resources↗

OPNET/Simulink Based Testbed for Disturbance Detection in the Smart Grid

The important backbone of the smart grid is the cyber/information infrastructure, which is primarily used to communicate with different grid components. A smart grid is a complex cyber physical system containing a numerous and variety number of sources, devices, controllers and loads. Therefore, the smart grid is vulnerable to grid related disturbances. For such dynamic system, disturbance and intrusion detection is a paramount issue. This paper presents a Simulink and Opnet based co-simulated platform to carry out a cyber-intrusion in cyber network for modern power systems and the smart grid. The IEEE 30 bus power system model is used to demonstrate the effectiveness of the simulated testbed. The experiments were performed by disturbing the circuit breakers reclosing time through a cyber-attack. Different disturbance situations in the considered test system are considered and the results indicate the effectiveness of the proposed co-simulated scheme.

Cyber Attacks↗

Eastern Renewable Generation Integration Study: Flexibility and High Penetrations of Wind and Solar; NREL (National Renewable Energy Laboratory)

Balancing wind and solar in a model is relatively easy. All you need to do is assume a very large system with infinite flexibility! But what if you don't have an infinitely flexible system? What if there are thousands of generators nestled in a handful of regions that are unlikely to change their operational practices? Would you still have enough flexibility to balance hundreds of gigawatts of wind and solar at a 5 minute level? At NREL, we think we can, and our industry partners agree. This presentation was presented at the IEEE Power and Energy Society General Meeting by Aaron Bloom, highlighting results of the Eastern Renewable Generation Integration Study.

14 SOLAR ENERGY↗

F3D Image Processing and Analysis for Many - and Multi-core Platforms

F3D is written in OpenCL, so it achieve[sic] platform-portable parallelism on modern mutli-core CPUs and many-core GPUs. The interface and mechanims to access F3D core are written in Java as a plugin for Fiji/ImageJ to deliver several key image-processing algorithms necessary to remove artifacts from micro-tomography data. The algorithms consist of data parallel aware filters that can efficiently utilizes[sic] resources and can work on out of core datasets and scale efficiently across multiple accelerators. Optimizing for data parallel filters, streaming out of core datasets, and efficient resource and memory and data managements over complex execution sequence of filters greatly expedites any scientific workflow with image processing requirements. F3D performs several different types of 3D image processing operations, such as non-linear filtering using bilateral filtering and/or median filtering and/or morphological operators (MM). F3D gray-level MM operators are one-pass constant time methods that can perform morphological transformations with a line-structuring element oriented in discrete directions. Additionally, MM operators can be applied to gray-scale images, and consist of two parts: (a) a reference shape or structuring element, which is translated over the image, and (b) a mechanism, or operation, that defines the comparisons to be performed between the image and the structuring element. This tool provides a critical component within many complex pipelines such as those for performing automated segmentation of image stacks. F3D is also called a "descendent" of Quant-CT, another software we developed in the past. These two modules are to be integrated in a next version. Further details were reported in: D.M. Ushizima, T. Perciano, H. Krishnan, B. Loring, H. Bale, D. Parkinson, and J. Sethian. Structure recognition from high-resolution images of ceramic composites. IEEE International Conference on Big Data, October 2014.

Source record↗