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NASA NTRS2008

Fiber-Optic Determination of N2, O2, and Fuel Vapor in the Ullage of Liquid-Fuel Tanks

A fiber-optic sensor system has been developed that can remotely measure the concentration of molecular oxygen (O2), nitrogen (N2), hydrocarbon vapor, and other gases (CO2, CO, H2O, chlorofluorocarbons, etc.) in the ullage of a liquid-fuel tank. The system provides an accurate and quantitative identification of the above gases with an accuracy of better than 1 percent by volume (for O2 or N2) in real-time (5 seconds). In an effort to prevent aircraft fuel tank fires or explosions similar to the tragic TWA Flight 800 explosion in 1996, OBIGGS are currently being developed for large commercial aircraft to prevent dangerous conditions from forming inside fuel tanks by providing an inerting gas blanket that is low in oxygen, thus preventing the ignition of the fuel/air mixture in the ullage. OBIGGS have been used in military aircraft for many years and are now standard equipment on some newer large commercial aircraft (such as the Boeing 787). Currently, OBIGGS are being developed for retrofitting to existing commercial aircraft fleets in response to pending mandates from the FAA. Most OBIGGS use an air separation module (ASM) that separates O2 from N2 to make nitrogen-enriched air from compressed air flow diverted from the engine (bleed air). Current OBIGGS systems do not have a closed-loop feedback control, in part, due to the lack of suitable process sensors that can reliably measure N2 or O2 and at the same time, do not constitute an inherent source of ignition. Thus, current OBIGGS operate with a high factor-of-safety dictated by process protocol to ensure adequate fuel-tank inerting. This approach is inherently inefficient as it consumes more engine bleed air than is necessary compared to a closed-loop controlled approach. The reduction of bleed air usage is important as it reduces fuel consumption, which translates to both increased flight range and lower operational costs. Numerous approaches to developing OBIGGS feedback-control sensors have been under development by many research groups and companies. However, the direct measurement of nitrogen (N2) is a challenge to most OBIGGS ullage sensors (such as tunable diode laser absorption) as they cannot measure N2 directly but depend on the measurement of oxygen (O2). The problem with a singular measure of O2, is that as the concentration (number density) of O2 decreases due to the inerting process or due to lower pressures from high altitudes, the precision and accuracy of the O2 measurement decreases. However, measuring O2 density in combination with N2 density (which is more abundant in air and in a N2-inerted fuel tank) can provide a much more accurate and reliable determination of the OBIGGS efficacy.

Nguyen, Quang-Viet↗

NASA NTRS2001

Integration of the QMSFRG Database into the HZETRN Code

Accurate nuclear interaction data bases are needed for describing the transport of space radiation in matter including space craft structures, atmospheres, and tissues. Transport models support the identification and development of new material concepts for human and electronic part protection. Quantum effects are manifested in nuclear reactions in several ways including interference effects between terms in the multiple scattering series, the many-body nuclear wave functions (for e.g. the roles of shell structure and Fermi momentum) and nuclear clustering. The quantum multiple scattering fragmentation model (QMSFRG) is a comprehensive model for generating nuclear interaction databases for galactic cosmic ray (GCR) transport. Other nuclear databases including the NUCFRG model and Monte-Carlo simulation codes such as FLUKA, LAHET, HETC, and GEANT ignore quantum effects. These codes fail to describe many important features of nuclear reactions and are thus inaccurate for the evaluation of materials for radiation protection. Previously we have shown that quantum effects are manifested through constructive interference in forward production spectra, the effects of Fermi momentum on production spectra, cluster nuclei knockout, and the nuclear response function. Quantum effects are especially important for heavy ions with mass numbers less than 20 that dominate radiation transport in human tissues and for the materials that are expected to be superior in space radiation protection. We describe the integration of the QMSFRG model into the HZETRN transport code. Integration milestones include proper treatment of odd-even charge-mass effects in nuclear fragmentation and the momentum distribution of nucleon production from GCR primary heavy ions. We have also modified the two-body amplitudes in the model to include nuclear medium effects. In order to include a comprehensive description of the GCR isotopic composition in materials, we have described the isotopic composition of the GCR by extending the 59-isotope version of HZETRN to an 120-isotope version. The isotopic composition of most primary GCR elements (including H, He, C, N, O, Ne, Mg, Si, Ar, Ca, Cr, and Fe) are included in the extended model. We discuss results for the high-energy neutron composition inside materials, and the charge and mass distribution for benchmark GCR problems.

Cucinotta, F. A.↗

NASA NTRS2014

Public-Private Collaborations with Earth-Space Benefits

The NASA Human Health and Performance Center (NHHPC) was established in October 2010 to promote collaborative problem solving and project development to advance human health and performance innovations benefiting life in space and on Earth. The NHHPC, which now boasts over 150 corporate, government, academic and non-profit members, has convened four successful workshops and engaged in multiple collaborative projects. The virtual center facilitates member engagement through a variety of vehicles, including annual in-person workshops, webcasts, quarterly electronic newsletters, web postings, and the new system for partner engagement. NHHPC workshops serve to bring member organizations together to share best practices, discuss common goals, and facilitate development of the collaborative projects. The most recent NHHPC workshop was conducted in November 2013 on the topic of "Accelerating Innovation: New Organizational Business Models," and focused on various collaborative approaches successfully used by organizations to achieve their goals. Past workshops have addressed smart media and health applications, connecting through collaboration, microbiology innovations, and strategies and best practices in open innovation. A fifth workshop in Houston, Texas, planned for September 18, 2014, will feature "Innovation Through Co-Development: Engaging Partners". One area of great interest to NASA is mobile health applications, including mobile laboratory analytics, health monitoring, and close loop sensing, all of which also offer ground-based health applications for remote and underserved areas. Another project being coordinated by NASA and the Health and Environmental Sciences Institute is the pursuit of one to several novel strategies to increase medication stability that would enable health care in remote terrestrial settings as well as during space flight. NASA has also funded work with corporate NHHPC partner GE, seeking to develop ultrasound methodologies that will enable NASA to further understand the eye changes related to long-duration space flight. The adaptation of ultrasound to this type of eye examination could also expand the use of ultrasound in health care on the Earth in settings where MRIs are not available. To further engage NHHPC members and facilitate partnership development for NASA, the NHHPC created and deployed an engagement system in 2014 that facilitates identification and evaluation of technical needs and opportunities among all NHHPC members.

Davis, Jeffrey R.↗

NASA NTRS2014

Enhancement of the Earth Science and Remote Sensing Group's Website and Related Projects

The major problem addressed throughout the term was the need to update the group's current website, as it was outdated and required streamlining and modernization. The old Gateway to Astronaut Photography of the Earth website had multiple components, many of which involved searches through expansive databases. The amount of work required to update the website was large and due to a desired release date, assistance was needed to help build new pages and to transfer old information. Additionally, one of the tools listed on the website called Image Detective had been underutilized in the past. It was important to address why the public was not using the tool and how it could potentially become more of a resource for the team. In order to help with updating the website, it was necessary to first learn HTML. After assisting with small edits, I began creating new pages. I utilized the "view page source" and "developer" tools in the internet browser to observe how other websites created their features and to test changes without editing the code. I then edited the code to create an interactive feature on the new page. For the Image Detective Page I began an evaluation of the current page. I also asked my fellow interns and friends at my University to offer their input. I took all of the opinions into account and wrote up a document regarding my recommendations. The recommendations will be considered as I help to improve the Image Detective page for the updated website. In addition to the website, other projects included the need for additional, and updated image collections, along with various project requests. The image collections have been used by educators in the classroom and the impact crater collection was highly requested. The glaciers collection focused mostly on South American glaciers and needed to include more of the earth's many glaciers. The collections had not been updated or created due to the fact that related imagery had not been catalogued. The process of cataloging involves identifying the center point location of the image and feature identification. Other project needs included collecting night images of India in for publishing. Again, many of the images were not catalogued and the database was lacking in night time imagery for that region. The last project was to calculate the size of mega fans in South Africa. Calculating the fan sizes involved several steps. To expedite the study, calculations needed to be made after the base maps had been created. Using data files that included an outline of the mega fans on a topographic map, I opened the file in Photoshop, determined the number of pixels within the outlined area, created a one degree squared box, determined the pixels within the box, converted the pixels within the box to kilometers, and then calculated the fan size using this information. Overall, the internship has been a learning experience for me. I have learned how to use new programs and I developed new skills. These These skills can help me as I enter into the next phase of my career. Learning Photoshop and HTML in addition to coding in Dreamweaver are highly sought after skills that are used in a variety of fields. Additionally, the exposure to different aspects of the team and working with different people helped me to gain a broader set of skills and allowed me to work with people with different experiences. The various projects I have worked on this summer have directly benefitted the team whether it was completing projects they did not have the time to do, or by helping the team reach deadlines sooner. The new website will be the best place to see all of my work as it will include the newly designed pages and will feature my updates to collections.

Coffin, Ashley↗

DOE OSTI2020

Radioactive Source Localization via Bayesian Particle Filter

In the event of a misplaced radioactive source or other emergency situation, measuring a radiation field, mapping its distribution, and determining a source location are essential tasks to ameliorating the situation. However, radiation fields may be extremely hazardous to human surveyors and minimizing received radiation doses is just as essential. Robots appear to be a potential solution to these problems. Beyond simply measuring radiation, the robot's computer processing capabilities offer a way to apply complex data analysis methods to radiation measurements in real-time. Methods which predict likely source locations can then feed this information into other processes, potentially improving path planning and enabling more efficient measurements. Given a robot mounted with a gamma-ray detector, can we: develop a methodology to account for detector performance across a wide range of source angles, distances, and photon energies? operate an autonomously navigating robot to effectively survey and characterize an area of interest? implement a data analysis method, conventionally used in measurements of motion, for source localization purposes? An open-source TurtleBot 3 robot, running Robot Operating System (ROS) on Ubuntu 16.04 LTS, was fitted with a Kromek GR1{sup R} Cadmium Zinc Telluride (CZT) solid-state gamma-ray detector. As a part of ROS, the packages OpenSlam, gmapping, and amcl were used to perform Simultaneous Localization and Mapping (SLAM), determining the robot's position and mapping the surrounding area. Data was acquired via Lidar mounted on top the TurtleBot 3. Detector Calibration Fit: The equation was fit to 365 counts of various energies, distances, and angles. A MATLAB{sup R} program was written to simulate measurements taken a robot on a random walk, with count data and positions discretized into finite element pixels. Using this program, a sample of 100 runs was performed on a map with a simulated source at the center, with a total of 200 of 2 pixels each. Similarly, multiple runs of the filter were performed on recorded robot measurement data. In both simulation and real tests, when corrected for errors (particles placed outside of bounds or on the robot, and simulation-specific errors), corresponding t-tests of predicted x and y-coordinates were within a 95% confidence interval of the actual position. For the real trial, these positions are slightly skewed right in the x-axis as the robot remained mainly to the left side of the source within the sample area. These simulations demonstrate potential validity for the usage of a particle filter as method of radioactive source localization. In the future, true real-time implementation and data fusion may further augment the performance of the robot to localize lost sources. Additionally, identification of multiple sources, determination of source types, and usage of a collimator are areas to potentially be explored.

12 MANAGEMENT OF RADIOACTIVE AND NON-RADIOACTIVE W↗

NASA NTRS2012

Extended-Range Passive RFID and Sensor Tags

Extended-range passive radio-frequency identification (RFID) tags and related sensor tags are undergoing development. A tag of this type incorporates a retroreflective antenna array, so that it reflects significantly more signal power back toward an interrogating radio transceiver than does a comparable passive RFID tag of prior design, which does not incorporate a retroreflective antenna array. Therefore, for a given amount of power radiated by the transmitter in the interrogating transceiver, a tag of this type can be interrogated at a distance greater than that of the comparable passive RFID or sensor tag of prior design. The retroreflective antenna array is, more specifically, a Van Atta array, named after its inventor and first published in a patent issued in 1959. In its simplest form, a Van Atta array comprises two antenna elements connected by a transmission line so that the signal received by each antenna element is reradiated by the other antenna element (see Figure 1). The phase relationships among the received and reradiated signals are such as to produce constructive interference of the reradiated signals; that is, to concentrate the reradiated signal power in a direction back toward the source. Hence, an RFID tag equipped with a Van Atta antenna array automatically tracks the interrogating transceiver. The effective gain of a Van Atta array is the same as that of a traditional phased antenna array having the same number of antenna elements. Additional pairs of antenna elements connected by equal-length transmission lines can be incorporated into a Van Atta array to increase its directionality. Like some RFID tags here-to-fore commercially available, an RFID or sensor tag of the present developmental type includes one-port surface-acoustic-wave (SAW) devices. In simplified terms, the mode of operation of a basic one-port SAW device as used heretofore in an RFID device is the following: An interrogating radio signal is converted, at an input end, from an electrical signal to an acoustic wave that propagates along a surface and encounters multiple reflectors suitably positioned along the surface. Upon returning to the input end, the reflected acoustic wave is re-converted to an electrical signal, which, in turn, is reradiated from an antenna. The distances between the reflectors in the SAW device and the corresponding times between reflections encode the identifying or sensory information onto the reradiated signal. The fundamental problem in the present development is how to combine a Van Atta antenna array (which is inherently a multiple-port device) and one or more one-port SAW device(s) into a single, compact, passive unit that can function as a retroreflective RFID tag. The solution is to use one or more hybrid, half-power 90 couplers. A basic unit of this type, shown in Figure 2, includes a half-power 90 hybrid coupler; two identical SAW devices (SAW1 and SAW2) connected to ports 3 and 4 of the coupler, respectively; and antenna elements connected to ports 1 and 2 of the coupler. Necessarily omitting details for the sake of brevity, it must suffice to report that the phase relationships among the coupler inputs and outputs are such as to couple the incident signal from the antenna elements to the SAW devices and couple the reflected signals from the SAW devices back to the antenna elements in the phase relationships required for a Van Atta array. Hence, the reradiated signal is automatically directed back toward the interrogating transceiver and contains identifying and/or sensory information encoded in time intervals between reflections.

Fink, Patrick W.↗

DOE OSTI2025

Pantex Plant Ogallala Aquifer and Perched Groundwater Contingency Plan

The Pantex Plant Ogallala Aquifer and Perched Groundwater Contingency Plan has been developed in accordance with the requirements identified in the: • Interagency Agreement for the Pantex Superfund Site, Article 8.5 Work to be Performed, • Compliance Plan Provision of Hazardous Waste Permit No. 50284, and • Record of Decision for Groundwater, Soil, and Associated Media, Pantex Plant. A Long‐Term Monitoring System Design has been designed to monitor conditions in the perched groundwater including changes in the perched aquifer as a result of implementing the response actions. Monitoring is required for verifying the effectiveness of perched groundwater response actions (i.e., conditions in the perched aquifer are being affected as intended) and for confirming that the perched aquifer and Ogallala Aquifer characterization as defined in the Resource Conservation and Recovery Act Facility Investigation Report and the Corrective Measure Studies/Feasibility Study remains accurate. If monitoring results obtained through the monitoring network identify an unexpected condition or deviation, contingent actions will be considered and implemented as necessary to ensure continued protection of the Ogallala Aquifer and human health and the environment. Potential deviations to expected technology performance may be encountered for each of the four primary response actions that compose the selected remedy for perched groundwater; Playa 1 Pump and Treat System, Southeast Area Pump and Treat System, Southeast Area In‐Situ Bioremediation System (comprised of the Southeast In‐Situ Bioremediation System Original System, Southeast Area In‐Situ Bioremediation System Extension System, Offsite In‐Situ Bioremediation System, Perchlorate/Chromium ISB, Northeast ISB and County Road 8 ISB), and Zone 11 In‐Situ Bioremediation System. Monitoring will also be conducted to determine if there are deviations to the expected characterization, e.g., contaminants not expected as a result of the RCRA Facility Investigation characterization. Deviations to expected conditions in the Ogallala Aquifer could also be encountered if the response actions in the perched groundwater are not performing as expected, i.e., preventing contaminants from migrating to the Ogallala Aquifer. Currently, Pantex has begun investigation of detections of high explosives above groundwater protection standards in wells on the Texas Tech University property and a plume that is moving to the northeast from that area. Due to those detections, this Plan recognizes the fact that future detections in the Ogallala will be focused on first‐ time detections of analytes. After a remedy is determined, this Plan will require modification to address-deviations and contingent actions. This Plan was developed to identify the contingent actions necessary to mitigate impacts resulting from deviations to site conditions or response action performance. The Plan defines the environmental problem being addressed by the response actions, clarifies the expected conditions and objectives of the response actions, and identifies the potential deviations to the response actions (due to site conditions or technology performance) that could be encountered. The deviations were evaluated to determine the likelihood of occurrence, potential impact, and time to respond to avoid impact. The Plan also identifies the monitoring outlined in the Long‐Term Monitoring System Design Report (Consolidated Nuclear Security, 2024) and Sampling Analysis Plan (PanTeXas Deterrence, 2024) that will be used to detect the deviations. Lastly, the Plan specifies the contingent actions that could be implemented in response to the deviations. Because each response focuses on a discrete portion of the perched aquifer and contaminant plume, each response action has a different set of expected conditions, and therefore differing impacts from deviations to the site and technology expectations. As a result, the contingent actions are identified for each response action and potential deviation including specific constituents, location, and conditions. If deviations are encountered that impact the ability of the response action to meet performance objectives, the contingent actions will be focused on ensuring the response action can meet the performance objective. Contingent actions may be implemented as interim actions (ISMs/removal actions) in accordance with the Record of Decision, Interagency Agreement, and Hazardous Waste Permit‐50284, if warranted by the specific circumstances. For deviations to site characterization expected conditions, the contingent action will focus on determination of the source of the deviation, determination of the appropriate response, and evaluation of additional work to be completed. However, if the deviation to characterization impacts the performance of the response action, the contingent action will again focus on ensuring performance objectives can be met. Early source term removals and cleanup actions have been implemented to protect the Ogallala Aquifer. Because of these actions and based on modeling results, the expected conditions in the Ogallala Aquifer are that constituents of concern will not be detected above the Groundwater Protection Standards (GWPSs) nor will they reach potential points of exposure above the GWPS. The primary deviation of concern for the Ogallala is if constituents are detected in the Ogallala Aquifer near or above GWPSs. If it occurs, this change in expected conditions would require further evaluation of site and contaminant characteristics to determine an appropriate course of action. The evaluation would include additional monitoring, source identification, implementation of interim protective measures (if necessary), and delineation of extent. These evaluations are necessary to determine an appropriate response action for the Ogallala. The primary goal of the Plan is to provide for the continued protection of the Ogallala Aquifer and the health of its consumers. In recognition, this Plan presents a flexible and rational approach for making future decisions associated with confirming the change in perched and Ogallala aquifer conditions and identifying a response (technical activities, changes to response actions, regulatory oversight, and public involvement).

12 MANAGEMENT OF RADIOACTIVE AND NON-RADIOACTIVE W↗

DOE OSTI2021

Estimation of constituent properties of concrete materials with an artificial neural network based method

Multi-scale models are developed for heterogeneous concrete materials to estimate their macroscopic mechanical properties in terms of micro-structural data. One crucial challenge of those models is the identification of local properties of constituent phases. In this paper, we present an efficient method based on Artificial Neural Networks (ANN). Typical concrete materials are taken as example. A macroscopic analytical strength criterion is established from three steps of nonlinear homogenization procedure. The macroscopic strength of materials is determined as a function of the frictional coefficient and cohesion of solid cement particles at nanometer scale, intra-particle pores, inter-particle pores and aggregates (inclusions). The objective is to identify the nanoscopic frictional coefficient and cohesion of cement particle from measured macroscopic values of uniaxial compression and tensile strengths. For this purpose, a numerical method based on the ANN is developed. With the analytical macroscopic strength criterion, sensitivity studies are first realized to identify the most important micro-structural parameters influencing the macroscopic strength of concrete. A simplified analytical macroscopic strength criterion is then proposed. A large dataset is further constructed through the inversion of the analytical strength criterion by using the aggregates volume fraction, porosity, macroscopic uniaxial tensile and compressive strengths as input variables and the frictional coefficient and cohesion of cement particles as output unknowns. An ANN model containing four hidden layers and 100 neurons in each layer is constructed and trained by using this dataset. Various types of validation of the ANN model are performed. It is found that the proposed ANN based model can effectively predict the frictional coefficient and cohesion of porous cement paste at the microscopic scale with a very good accuracy.

36 MATERIALS SCIENCE↗

NASA NTRSDate not supplied

Trajectory Engineering with Modular Patched Conics for Entry Systems and TPS (TEMPEST)

Brief Presenter Biography (35 word limit): Bohdan Wesely is an Aerospace Engineer in the Entry Systems and Technology Division at Ames. He has worked on a variety of projects for NASA including integrated TPS (thermal protection system) flight hardware deliveries and testing services for commercial partners. Introduction: TEMPEST is a new trajectory analysis framework that is designed to fill the gap between dedicated flight mechanics tools and aerothermal and TPS sizing tools. The project started as an SJSU master’s thesis and has since evolved into a general conceptual design tool capable of studying a wide variety of entry problems. Development is ongoing in the Entry Systems and Technology Division at NASA ARC. Why TEMPEST: Space missions involving entry into a planetary atmosphere involve a series of unique requirements across multiple disciplines. Whether it is traditional entry descent and landing (EDL), or aerocapture, the vehicle must navigate to its target landing location or orbit state, and the TPS must protect the payload during entry. The design process typically involves iterative handoffs between various flight mechanics, flow solver, and material response level tools. During the early conceptual phase, a wide variety of feasible trajectories are simulated in a Monte Carlo scenario which broadly satisfy the mission or landing requirements. Next, computational fluid dynamics (CFD), direct simulation Monte Carlo (DSMC), and other flow solver analyses are performed at various key trajectory points to generate an aero-database, heating and TPS design requirements also emerge at this stage. At this point, with updated aerodynamics from the various flow solvers, trajectories can be re-run, this in turn can change the required freestream conditions for the CFD tools, and as a project progresses, these analyses converge, and uncertainty is reduced. However, there is always a “hand-off” occurring between two inherently coupled phenomena. Analysis Description: One of the goals with TEMPEST is to use a variety of first principles estimation methods coupled with an atmosphere model to predict vehicle aerothermodynamics across the entire flight regime while propagating a 3 or 6 degree of freedom (DoF) trajectory. Aerodynamics methods include modified Newtonian, Maxwell and Cercignani- Lampis-Lord (CLL) for continuum, transitional, and free molecular flow regimes. Aerothermodynamics include boundary layer and reference enthalpy methods, and Mutation++ for non-equilibrium chemistry modeling. TEMPEST is also capable of stitching multiple trajectory segments together to study mission scenarios like multi-pass aerocapture and aero-gravity assists. Most of the program is implemented in MATLAB using modern system objects, it relies on several C++ shared libraries for supporting tools like Gmsh, the Global Reference Atmospheric Model (GRAM), and Mutation++. The various first principles aerothermal estimation methods are discretized across either a structured axisymmetric panel mesh or an unstructured tri-mesh generated from an open-source tool such as Gmsh, this allows solutions on the same mesh to be compared across tools such as CB-Aero. CFD Coupling. A physics-aware, gaussian process CFD anchoring scheme is proposed to adjust the various first principles methods as a CFD database is populated. One goal for this anchoring module is to inform the project where CFD should be run. Full knowledge of the entire trajectory, atmosphere, and aerothermodynamics allows for easier identification of high sensitivity areas and uncertainty quantification. While the first principles effects are well known and proven accurate in existing tools such as CB- Aero and Cart3D, a physics aware CFD anchoring scheme increases tool credibility across a project lifecycle. Material Response Modeling. Correct TPS sizing is critical for optimizing mass for science payloads and ensuring mission success. The process typically involves a thermal analysis along the trajectory with surface heating environments as a boundary condition. Several design constraints are maximum bondline temperature and maximum recession with various margining techniques. The material response tool FIAT, developed out of NASA Ames, is currently being integrated into the TEMPEST environment. TPS recession, shape change, mass loss, and mass property alteration are all factors that can perturb an entry trajectory. For missions like Mars 2020, recession was minimal and was safely handled separately as a post process. For missions such as Jupiter Galileo with a high TPS mass fraction or asteroid entries, recession plays a major role. The proposed fully coupled scheme is to use an epoch-based approach where the trajectory integration is halted after a recession threshold, the energy balance and FIAT are solved at each panel, the mesh, aerodynamics, and mass properties are updated, and the trajectory continues. Several computational tradeoffs have been made during the development of TEMPEST to limit the cost of a single trajectory and preserve its utility as a conceptual, rapid iteration tool. Conclusion: Development of TEMPEST is ongoing and the project is still in its infancy. This talk aims to showcase its unique capabilities to support future NASA entry systems missions.

Bohdan O Wesely↗

DOE OSTI2021

Robust Distributed State Estimator for Interconnected Transmission and Distribution Networks (Final Report RPPR-1)

This project’s objective is to develop a combined transmission and distribution state estimator which accounts for very large system size and model complexity (by way of distributing the computations) and large number of solar PV units connected to the distribution system on multiple feeders. The project not only provides a robust formulation and solution to this problem but also tests the solution by implementing it on a well-established large utility system. It introduces several improvements with respect to the state of the art in existing state estimation software: (a) The developed state estimator (SE) allows robust and accurate monitoring of bidirectional flows in distribution systems which result due to the distributed energy sources which are not observable and thus not incorporated in generation dispatch; (b) Large utility systems with tens of thousands of transmission buses and hundreds of thousands of distribution nodes are difficult to model as a single integrated system. This shortcoming is addressed by developing a “scalable distributed computational framework” which allows splitting the ultra large system models into several small subsystems and coordinating their solution by a robust and practical state estimation formulation; (c) Measurement errors irrespective of their locations are detected and removed by the developed state estimator. Historically, transmission and distribution systems were analyzed and operated as two independent systems. Given the non-transposed short feeder sections, unevenly loaded phases, strictly radial configuration and unidirectional power flows in the absence of remote generation, distribution system analysis was customized to account for these characteristics. However, some of these assumptions are no longer valid (non-radial configuration, bidirectional power flows) and thus distribution system analysis should be revisited. Furthermore, in the past, the interaction between the transmission and distribution systems was quite passive, where distribution substations were modeled as lumped loads in the transmission system model. With substantial generation injected by renewable generation located in the distribution systems, such modeling will no longer be accurate. The developed state estimator facilitates proper monitoring of the interactions between the transmission and distribution systems and enables smart dispatch of these units which are made observable by the state estimator.

24 POWER TRANSMISSION AND DISTRIBUTION↗

DOE OSTI2021

Sensor enabled data-driven predictive analytics for modeling and control with high penetration of DERs in distribution systems

The electric power grid is undergoing a tremendous transformation due to the increasing penetration of renewable energy resources beginning with wind and more recently with the distributed energy resources (DERs) such as solar and battery storage. DERs have dramatically changed the role of the distribution systems in the overall power grid, and they are expected to contribute a significant portion of power generation in the future. If current trends for DERs continue, system operation and control will need to change dramatically for improved grid reliability and resiliency. As renewable resources increase in penetration, new and challenging operational, planning, and design problems are expected to emerge. Some of the key challenges that arise in the planning and operation of the future grid are: 1) Quantifying the impact of high DER penetration in distribution systems on bulk grid behavior over multiple time scales. 2) Identifying whether a particular DER configuration/settings have a large impact on the overall grid behavior. These challenges can be addressed in an offline manner using detailed T&D grid models and they can also be addressed in an online manner using sensor measurements. In particular, the advancement and planned growth in sensor technology in power grid over various voltage levels provide us with a unique opportunity to tackle these challenges from a data analytic perspective without needing detailed T&D grid models. A few questions that naturally arise when addressing the challenges from DERs using sensor data are: 1) How can we use limited sensor measurements to monitor & control voltage stability and small signal stability of the bulk system? 2) How can we ensure that the developed data analytic methods are robust to data availability and quality issues? 3) How can we compute the developed analytics in a scalable manner using streaming measurements? In this project, we addressed the aforementioned challenges arising from DERs and answered the questions raised above on how to effectively use the sensor measurements to enhance the reliability and performance of the electric grid. Thus, the overarching goal of this project is to develop effective reduced/representative system models from data that make the computational complexity sufficiently manageable so as to be useful to simulate, analyze, and even control complex non-linear power systems dynamics with large penetrations of DERs. In order to achieve the objective, the project team established a four-fold technical approach 1) Formulated a combined transmission-distribution co-simulation framework for data generation and validation, 2) Derived reduced/representative models of power systems based on data-driven methods for efficient computation and appropriate representation of system behavior, 3) Developed data driven characterization of power system behavior based on transfer operator theory, machine learning and optimization for model estimation, 4) Incorporated a scalable data management and processing architecture using distributed Kafka streaming applications that coordinate input data streams to the developed data analytics. The key accomplishments of the project are: 1) Development of a scalable multi-timescale T&D co-simulation framework (both for steady state and for dynamic co-simulation) using commercial solvers (PSSE and GridLAB-D). The steady-state T&D co-simulation interface is shared with our industry partner (PJM). 2) A structured reduced order dynamic model of distribution systems that can represent partial motor stalling along with a systematic procedure to derive the model parameters. 3) A PMU based online method to monitor, localize and mitigate fault-induced delayed voltage recovery using DER reactive support and load control in distribution systems. 4) Development of linear operator based robust methodologies for dynamic state estimation, uncertainty quantification, system identification and trajectory prediction for power system dynamics. 5) An adaptive damping control for utilizing wind energy resources to provide oscillation damping and system stability. 6) Implementation of Kafka-based framework for efficient processing of streaming data using Linux-based local virtual environment.

DER integration↗

DOE OSTI2025

Identifying spatiotemporal patterns in opioid vulnerability: investigating the links between disability, prescription opioids and opioid-related mortality

Background: The opioid crisis remains one of the most daunting and complex public health problems in the United States. This study investigates the national epidemic by analyzing vulnerability profiles of three key factors: opioid-related mortality rates, opioid prescription dispensing rates, and disability rank ordered rates. Methods: This study utilizes county level data, spanning the years 2014 through 2020, on the rates of opioid-related mortality, opioid prescription dispensing, and disability. To successfully estimate and predict trends in these opioid-related factors, we augment the Kalman Filter with a novel spatial component. To define opioid vulnerability profiles, we create heat maps of our filter’s predicted rates across the nation’s counties and identify the hotspots. In this context, hotspots are defined on a year-by-year basis as counties with rates in the top 5% nationally. Results: Our spatial Kalman filter demonstrates strong predictive performance. From 2014 to 2018, these predictions highlight consistent spatiotemporal patterns across all three factors, with Appalachia distinguished as the nation’s most vulnerable region. Starting in 2019 however, the dispensing rate profiles undergo a dramatic and chaotic shift. Conclusions: The initial primary drivers of opioid abuse in the Appalachian region were likely prescription opioids; however, it now appears that abuse is sustained by illegal drugs. Additionally, we find that the disabled subpopulation may be more at risk of opioid-related mortality than the general population. Public health initiatives must extend beyond controlling prescription practices to address the transition to and impact of illicit drug use.

60 APPLIED LIFE SCIENCES↗