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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.

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All sourcesNASA NTRSDOE OSTI
DOE OSTI2019

Advancing the State of Technology thru DOE funded algae cultivation R&D at the Arizona Center for Algae Technology and Innovation

The Department of Energy's Bioenergy Technologies Office (BETO) has a long and successful history of funding an algae R&D portfolio driving progress towards affordable and renewable energy and co-products from algae biomass. A core capability established by BETO was the support of testbed facilities including those established under the Algae Testbed Public Private Partnership (ATP3) led by Arizona State University (ASU) and its Arizona Center for Algae Technology and Innovation (AzCATI). ATP3 established the experimental and operational framework to carry out long term cultivation trials to assess the State of Technology (SOT) for algal biomass productivity and conducted such trails thru the ending of the six year program in Spring 2018, and demonstrated steady progress increasing annual average biomass yields from 8.5 to 11.7 g/m2-day - a 38% increase from 2015 to 2018. Since the summer of 2018, the SOT framework established under ATP3 continues under another BETO funded lab-led consortium called DISCOVR "Development of Integrated Screening, Cultivar Optimization, and Verification Research." The DISCOVR team constitutes a powerful partnership among four of the DOE’s seventeen national laboratories: Los Alamos National Laboratory, National Renewable Energy Laboratory, Pacific Northwest National Laboratory (DISCOVR lead institution), and Sandia National Laboratories. With ASU’s AzCATI, they have joined forces to investigate algae strains that could lead to sustainable and clean algal biofuel and continue to generate open and transparent cultivation data sets for use by the algae biotechnology R&D community. In this talk, we will revisit the SOT results from ATP3, the SOT framework transition to DISCOVR with recent results from first full year of SOT cultivation under DISCOVR. With our recent advancements utilizing better cultivars verified thru DISCOVR’s pipeline, better crop protection and improved operational conditions, the combined effect was a further improvement in annual average productivity and reliability, leading to a year over year improvement in annual productivity from the 2018 baseline of 11.7 g/m2-day (generated across a total of 219 cultivation days) to 15.9 g/m2-day (326 cultivation days) – a 36% improvement for 2019! We will discuss these results in detail and highlight where AzCATI and the DISCOVR SOT is headed in 2020 and beyond.

09 BIOMASS FUELS↗
DOE OSTI2020

Robust Assessment of Real-World Adversarial Examples

We explore rigorous, systematic, and controlled experimental evaluation of adversarial examples in the real world and propose a testing regimen for evaluation of real world adversarial objects. We show that for small scene/ environmental perturbations, large adversarial performance differences exist. Current state of adversarial reporting exists largely as a frequency count over a dynamic collections of scenes. Our work underscores the need for either a more complete report or a score that incorporates scene changes and baseline performance for models and environments tested by adversarial developers. We put forth a score that attempts to address the above issues in a straight-forward exemplar application for multiple generated adversary examples. We contribute the following: 1. a testbed for adversarial assessment, 2. a score for adversarial examples, and 3. a collection of additional evaluations on testbed data.

deep learning, adversarial machine learning, machi↗
DOE OSTI2021

Service-Based, Segmented, 5G Network-Based Architecture for Securing Distributed Energy Resources: Preprint

As the number of connected devices in the energy grid increase exponentially, so too are the cybersecurity risks. With the development of modern communications standards such as 5G and beyond the extent to which devices will continue to connect will continue to increase exponentially along with the inherent risks. However, 5G also includes features to help address cybersecurity concerns and therefore helping to mitigate many of these risks. This paper proposes a new service-based network architecture implementing network-slicing capabilities for connected systems and devices to improve performance, availability, security, and reliability of the grid devices and services. This paper considers the quality of service requirements and criticality of services needed for securely monitoring, operating, and securing Distributed Energy Resource (DER) devices. From developed use cases, network slicing is implemented based on these requirements and resource allocations. This work then highlights examples of how slicing can help prevent standard existing attack methods such as a denial-of-service or similar attack which limits resource availability and network bandwidth to the service and thus limiting its ability to affect other services by misbehaving. The designed network architecture use case will be further tested on a local virtualized testbed to verify secure operation and availability of services. Using hardware-in-the-loop devices and systems on this local testbed, this fully segmented, secure network may be realized and evaluated. Finally, this paper presents the results of this testing.

5G↗
DOE OSTI2022

Autonomous Microgrid Restoration Using Grid-Forming Inverters and Smart Circuit Breakers: Preprint

The proliferation of distributed inverter-based resources (IBRs) raises the questions if these IBRs can be used to blackstart microgrids and distribution feeders after major outages. In this paper, we propose and evaluate an autonomous microgrid restoration concept using grid-forming (GFM) IBRs and smart circuit creakers (SCBs). The concept is first explored in simulation platform and then a hardware testbed containing actual GFM inverters is developed to demonstrate these functionalities. A combination of dispatchable virtual oscillator control (dVOC) and droop-based control schemes have been designed for GFM inverter controls in the software simulations and hardware testbed. Subsequently, operation of SCBs using two distinct principles have been demonstrated that can restore or connect portions of the network.

grid reconfiguration↗
DOE OSTI2023

A Systematic Study to Determine 5G Baseline Performance for Scientific Computing

The fifth-generation (5G) cellular networks envisions achieving higher data rates, improved connectivity, reduced latency, and better quality of service (QoS) than the fourthgeneration (4G) cellular networks. Such improved performance can be utilized to address the challenges in applications such as electricity generation in power systems. The traditional power grids responsible for electricity generation suffer from drawbacks such as life-threatening blackout crises, and energy storage proliferation as they are not robust to extreme climatic conditions. A recent study proposed the idea of extending the capabilities of advanced wireless technologies such as the current 5G to develop a robust, energy-efficient, and secure smart grids. However there are two main challenges associated with the integration of power systems and wireless technologies. First, it is imperative to understand the architecture and the enabling technologies of 5G to ensure that the performance requirements of the smart grids are met. Second, an end-to-end testbed is required to determine if the performance requirements are met by estimating the 5G characteristics such as latency, and throughput. Our proposed alleviates the aforementioned concerns in the following manner. To begin with, a systematic study of the 5G architecture including both the StandAlone (SA) and Non-Standalone (NSA) operations is presented. Furthermore, a detailed survey of the possible 5G enabling technologies is elicited. In addition to these, an end-toend testbed that can estimate the 5G characteristics is explained in detail with appropriate preliminary results.

5G, 5G Communication↗
DOE OSTI2017

Design and analysis of embedded I and C for loop-scale magnetically suspended pump - 261

Improving nuclear reactor designs and fuel processing technologies for safer and more efficient operation require the development of new component designs. In particular, many of the advanced reactor design such as the molten salt reactors and high-temperature gas cooled reactors have operating environments beyond the ability of many currently commercially available components. To address this, new cross-cutting technologies need to be developed that will enable the design, fabrication, and reliable operation of new classes of reactor components. The Advanced Sensor Initiative of the Nuclear Energy Enabling Technologies initiative is investigating advanced sensor and control designs that are capable of operating in these extreme environments. Under this initiative Oak Ridge National Laboratory (ORNL) has been developing embedded instrumentation and control for extreme environments. To develop, test, and validate these new sensing and control techniques, ORNL is building a pump testbed with submerged magnetic bearings. The eventual goal is to apply these techniques to a high temperature (700 deg. C) canned rotor pump that utilizes active magnetic bearings to eliminate the need for mechanical bearings and seals. The technologies will benefit the Next Generation Power Plant, Advanced Reactor Concepts, and Small Modular Reactor programs. In this paper we will detail the design and analysis of the embedded I and C testbed with submerged magnetic bearings. Then we will analyze the fluid forces on the shaft. Finally, we will develop the radial and thrust bearing geometries needed to meet the force requirements. (authors)

21 SPECIFIC NUCLEAR REACTORS AND ASSOCIATED PLANTS↗
DOE OSTI2017

Initial Modeling of Urban Search Measurements

Detection of illicit nuclear materials in urban environments is difficult due to the large amount of background radiation from naturally occurring radioactive materials (NORM) in the roadways and buildings. Mobile searches suffer from low count rates, so the detection algorithms must be carefully balanced between missing real sources and reporting too many false alarms. The Modeling Urban Scenarios and Experiments (MUSE) project aims to create a virtual testbed for simulation of radiation detection to predict realistic background and threat source detection events so that detection algorithms can be better optimized to find illicit sources. The MUSE project is a collaboration of Oak Ridge National Laboratory (ORNL), Lawrence Berkeley National Laboratory (LBNL), and the Remote Sensing Laboratory (RSL). The project also works with staff at Lawrence Livermore National Laboratory (LLNL) to support the development of the Optimization Planning Tool for Urban Search (OPTUS) software package. The first step in creating a virtual testbed is to determine the level of detail required in the models to match actual measurements. Several measurement campaigns were conducted in 2015 and 2016 at the Fort Indiantown Gap (FTIG) Combined Arms Collective Traming Facility (CACTF). This facility contains a representative urban environment, with a dozen buildings and several streets. Detectors commonly used in search operations - 2 in x 4 in x 16 in NaI(Tl) - were used to measure count rates from background and sources. Measurements with a shielded high-purity germanium detector of the roadways, sidewalks, and building walls were made to determine the concentration of NORM that makes up the bulk of the background radiation. This paper shows some comparisons of modeling simulations to measurements taken during the OPTUS-3 campaign in November 2015. Measurements with and without an 81 {mu}Ci cesium source were made at several points along the center line of the main road. Initial results show good agreement between the measured and simulated spectra above 300 keV. Additional studies to determine the causes of mismatch below 300 keV have been started and will also be discussed.

07 ISOTOPE AND RADIATION SOURCES↗
DOE OSTI2017

Characterization of NORM in an Urban Environment using HPGe Measurements and MCNP6 Simulations

This work is part of a larger project aimed at producing an operationally relevant, validated simulation environment that can be used as a 'virtual testbed' for counterterrorism and counterproliferation efforts. Examples of such efforts include searches for illicit radiation sources before and during large special events, such as the presidential nominating conventions, inaugurations, and large sporting events. Once validated by laboratory and field measurements, this testbed can be used to test and validate algorithms and detector systems designed for various search missions in an urban environment. The detection of radioactive sources in a city is greatly complicated by natural background radiation, which emanates from various materials common to an urban environment, such as roadways, sidewalks, and building exteriors. The methods and results offered here represent the conclusion of an effort to characterize the concentration of naturally occurring radioactive material (NORM) in various elements in a controlled, but representative, urban environment. Some of the methods discussed in previous work will be briefly reiterated here, but more detail can be found in the preceding work. The location chosen for this effort was a Military Operations on Urban Terrain (MOUT) environment at the Fort Indiantown Gap (FTIG) National Guard training facility in Pennsylvania. This site was chosen because it replicates a small town where traffic and pedestrian access could be easily controlled, as to not interfere with the background measurements. This endeavor involved over 70 measurements using a high-purity germanium (HPGe) detector designed to ascertain the NORM concentrations in the soil, asphalt roads, gravel lots, concrete intersections, sidewalks, foundations, and walls found throughout the site. The NORM concentrations determined from this work will be incorporated into a large-scale simulation that can be used to investigate various search techniques and algorithms, detector types and setups, and to produce representative synthetic data for future work.

07 ISOTOPE AND RADIATION SOURCES↗
DOE OSTI2023

Use of Sensors and Machine Learning for Signal Discovery in a Solvent Extraction Process – 23280

Reprocessing is an important step in the nuclear fuel cycle where usable nuclear materials are extracted from spent fuel for recycling. The extraction of materials for reuse simultaneously reduces not only the volume of nuclear waste, but its decay time to radioactivity levels similar to that of the originating uranium ore. As part of an initiative to steward research, development, and innovation into the nuclear fuel cycle, Idaho National Laboratory is designing and constructing a solvent extraction testbed named Beartooth. Beartooth will allow researchers to refine extraction processes, test innovative extraction processes, and give early career scientists opportunities to gain skills in performing separations chemistry that uses centrifugal contactors. In addition, the Beartooth testbed is being uniquely designed to enable novel technologies including machine learning capabilities for the characterization of chemical process operations in near real-time. To aid in the design of Beartooth, a team of researchers are installing a variety of atypical sensors into a system of contactors for signal discovery. The team will implement machine learning methods on sensor data to determine signal features with the goal of providing a process operator with a deeper understanding of the chemical process and equipment usage. This work will summarize sensors utilized and preliminary results from an infrared camera.

11 NUCLEAR FUEL CYCLE AND FUEL MATERIALS↗
DOE OSTI2026

A Physics-Informed Reinforcement Learning Framework for Economic-Thermal Co-Optimization of Crypto Mining Data Centers: Preprint

The rapid expansion of cryptocurrency mining has created a new class of high-density data centers characterized by extreme thermal flux and high sensitivity to volatile economic markets. Traditional thermal management strategies, typically reliant on rule-based control, maintain static setpoints that fail to account for fluctuating electricity prices and cryptocurrency values - factors critical to mining profitability. To address this, we present a physics-informed reinforcement learning (PIRL) framework for economic-thermal co-optimization in crypto mining data centers. This framework consists of a proximal policy optimization (PPO) agent, a virtual testbed powered by high-fidelity physics-based models, and an interactive frontend dashboard. The PPO agent is trained using the virtual testbed and strict hardware safety limits. This physics-informed approach allows the agent to learn a stochastic policy that dynamically balances mining revenue against operational costs by co-optimizing HVAC cooling setpoints and IT computational hashrate. The simulation results demonstrate that the integrated framework achieved an 8.62% increase in net operational profit compared to traditional baseline strategies while strictly adhering to safety-critical temperature constraints (coolant supply temperature < 32 degrees C). This work provides a scalable template for the deployment of reinforcement learning in mission critical facilities where economic volatility and physical safety must be managed simultaneously.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗
DOE OSTI2019

Laboratory-Scale Microgrid System for Control of Power Distribution in Local Energy Networks - Part I: Theory and Design

One of the promising solutions to achieve sustainable energy systems in future smart cities is to deploy microgrids in local energy networks. Due to the decentralized nature of microgrids, large-scale utilization of these resources will increase the reliability of the energy systems as well as facilitating the integration of renewable energy resources to enable more environmentally-friendly energy network. This chapter presents development of a highly reconfigurable, laboratory-scale microgrid testbed. The proposed microgrid system integrates several distributed generation (DG) units representing photovoltaic panel, wind turbine, battery energy storage and etc. The schematic of the proposed system can be customized to investigate numerous grid architectures and control scenarios. In this study, the loads and energy resource allocation are realized by assessment of the loads and resources priority. Therefore, a hierarchical procedure will take place to allocate the power to different buses in microgrid. In the next chapter, we describe the test-bed implementation of the designed microgrid.

design↗
DOE OSTI2022

Moving Target Defense Routing for SDN-enabled Smart Grid

The increasing attack surface area in the smart grid communication networks is making the grid more susceptible to cyber attacks that can lead to instability of the grid and even blackouts. While there are multiple types of cyber attacks that can impact the grid, Denial of Service (DoS) attacks are relatively easier to inject as they require lesser knowledge about the system as compared to data integrity attacks. Various research works showcase methods to prevent or mitigate the impacts of DoS attacks in the smart grid but the research still lacks in demonstrating the feasibility and efficacy of the solutions in a real-world environment. In this paper, we propose a Moving Target Defense (MTD)-enabled Software Defined Network (SDN) for the Smart Grid communication implemented on a Hardwarein- the-Loop (HIL) Testbed. We showcase the implementation of the proposed architecture of MTD-enabled SDN using Mininet 2.3.0 which enables communication between the physical grid and the control center. The results show the advantages of using MTD based on SDN for the wide-area network (WAN) with much lower packet drop percentages in the case of MTD-based routing in the SDN WAN. Index Terms—SDN,

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2012

Distributing Power Grid State Estimation on HPC Clusters A System Architecture Prototype

The future power grid is expected to further expand with highly distributed energy sources and smart loads. The increased size and complexity lead to increased burden on existing computational resources in energy control centers. Thus the need to perform real-time assessment on such systems entails efficient means to distribute centralized functions such as state estimation in the power system. In this paper, we present our early prototype of a system architecture that connects distributed state estimators individually running parallel programs to solve non-linear estimation procedure. The prototype consists of a middleware and data processing toolkits that allows data exchange in the distributed state estimation. We build a test case based on the IEEE 118 bus system and partition the state estimation of the whole system model to available HPC clusters. The measurement from the testbed demonstrates the low overhead of our solution.

Distributed architecture↗
DOE OSTI2018

A Hierarchical Multi-Agent Based Anomaly Detection for Wide-Area Protection in Smart Grid

Future smart grid capabilities provide assurance to expand the advanced information and communication technologies to evolve into densely interconnected cyber physical system. Remedial Action Scheme (RAS), widely used for wide-area protection, relies on the interconnected networks and data sharing devices, which are exposed to the multitude of vulnerabilities. This paper presents our proposed approach to developing multi-agent based RAS scheme against the system-aware stealthy cyber-attacks. Specifically, we propose the two-level hierarchical architecture which consists of distributed local RAS controllers (RAScs) as local agents, operating at different zones/ areas, which are constantly monitored by an overseer, the central agent. The local controllers receive local and randomly changing outside zonal measurements and cyclically forwards to the overseer. The overseer identifies the corrupted controller using the anomaly detection algorithm which processes the measurements coming from the local controllers, compute measurement errors using local and outside zonal measurements, perform validation checks, and finally detect anomalies based on the two-step verification. Next, as a proof of concept, we have implemented and validated the proposed methodology in cyber physical environment at Iowa State’s PowerCyber testbed. We have also implemented the coordinated attack vectors which involve corrupting the local controller and later performing stealthy attacks on the system’s generator. We have evaluated its performance during the online testing in terms of detection rate and Iatency. The experimental results show that it is efficient in detecting different classes of attacks, including ramp and pulse attacks.

24 POWER TRANSMISSION AND DISTRIBUTION↗
DOE OSTI2020

A Novel Architecture for Attack-Resilient Wide-Area Protection and Control System in Smart Grid

Wide-area protection and control (WAPAC) systems are widely applied in the energy management system (EMS) that rely on a wide-area communication network to maintain system stability, security, and reliability. As technology and grid infrastructure evolve to develop more advanced WAPAC applications, however, so do the attack surfaces in the grid infrastructure. This paper presents an attack-resilient system (ARS) for the WAPAC cybersecurity by seamlessly integrating the network intrusion detection system (NIDS) with intrusion mitigation and prevention system (IMPS). In particular, the proposed NIDS utilizes signature and behavior-based rules to detect attack reconnaissance, communication failure, and data integrity attacks. Further, the proposed IMPS applies state transition-based mitigation and prevention strategies to quickly restore the normal grid operation after cyberattacks. As a proof of concept, we validate the proposed generic architecture of ARS by performing experimental case study for wide-area protection scheme (WAPS), one of the critical WAPAC applications, and evaluate the proposed NIDS and IMPS components of ARS in a cyber-physical testbed environment. Our experimental results reveal a promising performance in detecting and mitigating different classes of cyberattacks while supporting an alert visualization dashboard to provide an accurate situational awareness in real-time.

24 POWER TRANSMISSION AND DISTRIBUTION↗
DOE OSTI2015

Co-Simulation Platform For Characterizing Cyber Attacks in Cyber Physical Systems

Smart grid is a complex cyber physical system containing a numerous and variety of sources, devices, controllers and loads. Communication/Information infrastructure is the backbone of the smart grid system where different grid components are connected with each other through this structure. Therefore, the drawbacks of the information technology related issues are also becoming a part of the smart grid. Further, smart grid is also vulnerable to the grid related disturbances. For such a dynamic system, disturbance and intrusion detection is a paramount issue. This paper presents a Simulink and OPNET based co-simulated test bed to carry out a cyber-intrusion in a cyber-network for modern power systems and smart grid. The effect of the cyber intrusion on the physical power system is also presented. 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 in the cyber network. Different disturbance situations in the proposed test system are considered and the results indicate the effectiveness of the proposed co-simulated scheme.

cyber attack characterization↗
DOE OSTI2021

Test Article and Test Plan for Heat-Pipe Gap-Conductance Testing

The SPHERE Facility at INL is established to test phenomena related to heat pipes in nuclear applications. The current capability of the SPHERE testbed is operation of liquid alkali-metal-cooled heat pipes in a variety of atmospheres. The controlled atmosphere can be used to prevent oxidation of system parts and also to affect the thermal conductivity of gases for any interfacial gaps within the heat-pipe assembly. Currently available modes are vacuum, air, nitrogen, helium, and argon. Controlled mixtures of helium and argon are available to vary the thermal conductivity of the gas. The primary test article will be based on the existing 7-hole block design used for shakedown testing of the SPHERE Facility. The SPHERE test stand will be used with test articles to establish the conductivity between fuel elements as well as between the heat pipe and other layers of the fuel-rod assembly. Existing and new test blocks will be used and modified with additional instrumentation to establish the thermal conductivity between the gap of the block wall and the heat pipes.

21 SPECIFIC NUCLEAR REACTORS AND ASSOCIATED PLANTS↗
DOE OSTI2023

An Architectural Survey of the Pluto Test Bunker Facility, Nevada National Security Site, Nye County, Nevada

The U.S. Department of Energy (DOE), in conjunction with the National Nuclear Security Administration Nevada Field Office (NNSA/NFO), proposes to reactivate Building 26-2205 as part of a project to detect foundry-type operations with remote sensing. The project is known as the Signals Exploration Testbed, or SET for short. Building 26-2205 (State Historic Preservation Office [SHPO] Resource No. B11558) is the former Compressor Building for the Pluto Program in Area 26 of the Nevada National Security Site (NNSS). Proposed actions at Building 26-2205 include removal of exterior building and site features, such as fencing, concrete pads, a large steel tank, and visible utilities, as well as interior changes to the building’s floor plan. These activities constitute an undertaking subject to review under Section 106 of the National Historic Preservation Act (NHPA) (54 United States Code [USC] § 306101) and its implementing regulations, 36 Code of Federal Regulations (CFR) Part 800.

54 ENVIRONMENTAL SCIENCES↗