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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 OSTI2011

DOE: Integrating Southwest Power Pool Wind Energy into Southeast Electricity Markets

Wind power development in the United States is outpacing previous estimates for many regions, particularly those with good wind resources. The pace of wind power deployment may soon outstrip regional capabilities to provide transmission and integration services to achieve the most economic power system operation. Conversely, regions such as the Southeastern United States do not have good wind resources and will have difficulty meeting proposed federal Renewable Portfolio Standards with local supply. There is a growing need to explore innovative solutions for collaborating between regions to achieve the least cost solution for meeting such a renewable energy mandate. The DOE-funded project 'Integrating Southwest Power Pool Wind Energy into Southeast Electricity Markets' aims to evaluate the benefits of coordination of scheduling and balancing for Southwest Power Pool (SPP) wind transfers to Southeastern Electric Reliability Council (SERC) Balancing Authorities (BAs). The primary objective of this project is to analyze the benefits of different balancing approaches with increasing levels of inter-regional cooperation. Scenarios were defined, modeled and investigated to address production variability and uncertainty and the associated balancing of large quantities of wind power in SPP and delivery to energy markets in the southern regions of the SERC. The primary analysis of the project is based on unit commitment (UC) and economic dispatch (ED) simulations of the SPP-SERC regions as modeled for the year 2022. The UC/ED models utilized for the project were developed through extensive consultation with the project utility partners, to ensure the various regions and operational practices are represented as accurately as possible realizing that all such future scenario models are quite uncertain. SPP, Entergy, Oglethorpe Power Company (OPC), Southern Company, and the Tennessee Valley Authority (TVA) actively participated in the project providing input data for the models and review of simulation results and conclusions. While other SERC utility systems are modeled, the listed SERC utilities were explicitly included as active participants in the project due to the size of their load and relative proximity to SPP for importing wind energy. The analysis aspects of the project comprised 4 primary tasks: (1) Development of SCUC/SCED model of the SPP-SERC footprint for the year 2022 with only 7 GW of installed wind capacity in SPP for internal SPP consumption with no intended wind exports to SERC. This model is referred to as the 'Non-RES' model as it does not reflect the need for the SPP or SERC BAs to meet a federal Renewable Energy Standard (RES). (2) Analysis of hourly-resolution simulation results of the Non-RES model for the year 2022 to provide project stakeholders with confidence in the model and analytical framework for a scenario that is similar to the existing system and more easily evaluated than the high-wind transfer scenarios that are analyzed subsequently. (3) Development of SCUC/SCED model of the SPP-SERC footprint for the year 2022 with sufficient installed wind capacity in SPP (approximately 48 GW) for both SPP and the participating SERC BAs to meet an RES of 20% energy. This model is referred to as the 'High-Wind Transfer' model with several different scenarios represented. The development of the High-Wind Transfer model not only included identification and allocation of SPP wind to individual SERC BAs, but also included the evaluation of various methods to allow the model to export the SPP wind to SERC without developing an actual transmission plan to support the transfers. (4) Analysis of hourly-resolution simulation results of several different High-Wind Transfer model scenarios for the year 2022 to determine balancing costs and potential benefits of collaboration among SPP and SERC BAs to provide the required balancing.

17 WIND ENERGY↗
DOE OSTI2018

Multi-Level Load Balancing with an Integrated Runtime Approach

The recent trend of increasing numbers of cores per chip has resulted in vast amounts of on-node parallelism. These high core counts result in hardware variability that introduces imbalance. Applications are also becoming more complex, re-sulting in dynamic load imbalance. Load imbalance of any kind can result in loss of performance and system utilization. We address the challenge of handling both transient and persistent load imbalances while maintaining locality with low overhead. In this paper, we propose an integrated runtime system that combines the Charm++ distributed programming model with concurrent tasks to mitigate load imbalances within and across shared memory address spaces. It utilizes a periodic assignment of work to cores based on load measurement, in combination with user created tasks to handle load imbalance. We integrate OpenMP with Charm++ to enable creation of potential tasks via OpenMP's parallel loop construct. This is also available to MPI applications through the Adaptive MPI implementation. We demonstrate the benefits of our work on three applications. We show improvements of Lassen by 29.6% on Cori and 46.5% on Theta. We also demonstrate the benefits on a Charm++ application, ChaNGa by 25.7% on Theta, as well as an MPI proxy application, Kripke, using Adaptive MPI.

Bak, Seonmyeong↗
DOE OSTI2014

SU-E-T-186: Feasibility Study of Glass Cherenkov Detector for Prompt Gamma Detection in Proton Therapy

Purpose: To simulate a Cherenkov glass detector system utilizing prompt gamma (PG) technique to quantify range uncertainties in proton radiation therapy. Methods: A simulation of high energy photons typically produced in proton interactions with materials incident onto a block of Cherenkov glass was performed with the Geant4 toolkit. The standard electromagnetic package was used along with several decay modules (G4Decay, G4DecayPhysics, and G4RadioactiveDecayPhysics) and the optical photon components (G4OpticalPhysics). Our setup included a pencil beam consisting of a hundred thousand 6 MeV photons (approximately the deexcitation energy released from 16O) incident onto a 2.5 ⊗ 2.5 ⊗ 1.5 cm3 of a Cherenkov glass (7.2 g of In2O3 + 90 g cladding, density of 2.82 g/cm3, Zeff = 33.7, index of refraction 1.56). The energy deposited from incident 6 MeV photons as well as secondary electrons and resulting optical photons were recorded. Results: The energy deposited by 6 MeV photons in glass material showed several peaks that included the photoelectric, the single and double escape peaks. About 11% of incident photons interacted with glass material to deposit energy. Most of the photons collected were in the region of double escape peak (approximately 4.98 MeV). The secondary electron spectrum produced from incident photons showed a high energy peak located near 6 MeV and a sharp peak located ∼120 keV with a continuous distribution between these two points. The resulting Cherenkov photons produced showed a continuous energy distribution between 2 and 5 eV with a slight increase in yield beginning about 3 eV. The amount of Cherenkov photons produced per interacting incident 6 MeV photon was ∼240.7. Conclusion: This study suggests the viability of utilizing the Cherenkov glass material as a possible prompt gamma photon detection device. Future work will include optimization of the detector system to maximize photon detection efficiency.

46 INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AND ↗
DOE OSTI2023

Molecular redox-active organic materials for electrochemical carbon capture

Abstract This prospective is a forward-looking outlook for researchers investigating electrochemical carbon capture utilizing molecular redox-active organic materials, with the following objectives: (1) identifying the essential components of an electrochemical carbon capture system, (2) introducing design principles for the system utilizing redox-active organic materials, encompassing their physicochemical properties and other critical factors, (3) presenting representative examples, and (4) promoting further experimental and theoretical studies on the application of redox-active organic materials for electrochemical carbon capture. Graphical abstract

Seo, Hyowon (ORCID:0000000295691902)↗
DOE OSTI2023

Autonomous System Inference, Trojan, and Adversarial Reprogramming Attack and Defense (Final)

In the world of ever-advancing technology, Autonomous Systems (AS) find extensive application, bolstering functionalities of critical infrastructures such as nuclear power plants. These systems, however, are increasingly becoming a target for nefarious activities, namely through inference attacks, trojan attacks, and adversarial reprogramming. This paper delves into a comprehensive exploration of machine learning (ML)-driven autonomous control systems within advanced nuclear reactor designs, revealing the vulnerabilities and proposing strategies for defense against potential cyber-attacks. Advanced cyber-attacks against critical infrastructure and the energy sector are becoming more common. With the invention of autonomous control systems (ACS) within advanced nuclear reactor designs, system designers, reactor operators, and regulators must consider cybersecurity during the design and operational phases. This article provides a cyber threat assessment of machine learning (ML)- based digital twinning (DT) technologies in the context of advanced reactor ACS. A cyber-physical testbed was created to emulate nuclear reactor digital instrumentation and controls (I&C) and act as a basis for the ACS. The ACS was designed as two plant-level DTs predicting reactor malfunctions and determining control actions and two component-level DTs responsible for classifying component states and forecasting component inputs and outputs (I/O). Two duplicate ACS designs– one using a traditional ML framework and one using an automated ML (AutoML) framework– were created and tested against cyber-attacks on training data, real-time process data, and ML model architectures to determine their respective qualitative cyber-risk in terms of likelihood and impact. Both frameworks showed similar cyber-resilience against training, real-time, and ML architecture attacks, proving that neither is inherently more secure. Recommended safeguard and security measures are posed to system designers, reactor operators, and regulators to maintain the cybersecurity of ML-based DT technologies such as ACS, prompting a holistic view of shared responsibility for maintaining cyber-secure ML-based systems. As global reliance on generation III reactors begins to be critically assessed, the evolution towards advanced reactor systems utilizing digital instrumentation and controls (I&C) becomes not merely preferable, but essential. The integration of semi and fully autonomous control systems (ACS), powered by digital I&C and machine learning (ML)-based digital twinning (DT) technologies, emerges as a potent strategy to mitigate operations and maintenance costs, thereby enhancing the economic feasibility of novel reactor designs. However, with a staggering 500% and 380% increase in cyber-attacks reported against the energy sector by the United States Department of Energy (DoE) and the European Union respectively, a surge in cyber vulnerabilities specifically targeting the nuclear industry has been 2 markedly observed. Notable incidents, such as the W32.Ramnit spyware infiltration at the Gundremmingen nuclear power plant in Germany and the Dtrack spyware intrusion at the Kudankulam nuclear power plant in India, while not directly compromising core industrial control systems (ICS), underscore a compelling necessity to fortify cybersecurity protocols in safeguarding reactor systems against increasingly adept digital adversaries. In light of this, our investigation extends beyond conventional cybersecurity parameters, diving into the intricate web of potential vulnerabilities woven into ML-based DTs and ACS in advanced reactor systems. A crafted cyber-physical testbed and preliminary ACS were devised to act as a mirror, reflecting potential configurations of advanced reactor control designs. Moreover, this study is intertwined with a scrutinization of ML models, developed either through conventional, manually tuned methodologies or via automated means through AutoML, probing into their cyber-risk profiles within operational technology (OT) environments. Expanding on this, two distinct ACS blueprints were forged – one navigating through the corridors of traditional ML and the other traversing the path of AutoML – in an effort to holistically encapsulate the considerations pivotal to ML-based DT control system design. Employing the SANS Institute Industrial Control System (ICS) Kill Chain and the MITRE ATT&CK Tactics, Techniques, and Procedures (TTP) framework, a structured analysis was conducted, launching three targeted attacks against the training dataset, real-time dataset, and ML models, therein dissecting the potential cyber-attack implications against both ML frameworks within an ACS milieu. It is essential to note that three distinct categories of attacks were conducted against both ACS configurations, each encompassing three distinct ML-based DTs, cumulating in a total of 18 varied attacks. This exploration extends into the realms of Autonomous System Inference, Trojan, and Adversarial Reprogramming Attack and Defense, unraveling vulnerabilities, and opportunities for fortified defenses against such intrusions, particularly where ML-driven technologies, and by extension, ACS, are deployed. Final recommendations, articulated through a lens of security, safeguard, and implementation considerations, are presented for both traditional and AutoML models, anchoring upon the existing knowledge landscape and ML-based DT modeling for ACS, and are offered as a beacon to guide the nuclear industry through the intricate cybersecurity challenges that lie ahead.

22 GENERAL STUDIES OF NUCLEAR REACTORS↗
NASA NTRS1985

An intensified photodiode array detector for space applications

The Hopkins Ultraviolet Telescope (HUT) is a general purpose moderate resolution spectrograph which is now being constructed for launch on the Space Shuttle. The instrument contains a Rowland spectrograph, which is located at the prime focus of a 0.9-m f/2 parabola. A description is given of the progress which has been made in the development of a flight detector for HUT. The detector developed is an intensified photodiode array. The image intensifier part of the detector contains two 25-mm 80:1, 12-micron pore microchannel plates (PCPs). A thin layer of CsI deposited on the front surface of the first microchannel plate has the objective to increase the quantum efficiency of the detector below 1850 A. The detector system utilizes a spectrometer processor (SP) which is based upon a bit-sliced microprocessor. The current status of the HUT detector system is discussed, and aspects of performance are evaluated. It is felt that the developed system will meet or exceed the design requirements.

Long, K. S.↗
NASA NTRS1990

Bar-Code System Tracks Test Equipment

Administration of complicated system speeded and simplified. Computer system uses bar codes to keep track of more than 2,200 items of test equipment. BETUS (Barcode Equipment Tracking and Utilization System), maintains data base on what items borrowed, who is using them and where, and when calibrated. Keeps records on tools and small electronic components. Saves on equipment purchases and recovers missing equipment more quickly. Cuts check-in and checkout time by 90 percent.

Rogers, Jacob R.↗
NASA NTRS1991

Fuzzy logic applications to expert systems and control

A considerable amount of work on the development of fuzzy logic algorithms and application to space related control problems has been done at the Johnson Space Center (JSC) over the past few years. Particularly, guidance control systems for space vehicles during proximity operations, learning systems utilizing neural networks, control of data processing during rendezvous navigation, collision avoidance algorithms, camera tracking controllers, and tether controllers have been developed utilizing fuzzy logic technology. Several other areas in which fuzzy sets and related concepts are being considered at JSC are diagnostic systems, control of robot arms, pattern recognition, and image processing. It has become evident, based on the commercial applications of fuzzy technology in Japan and China during the last few years, that this technology should be exploited by the government as well as private industry for energy savings.

Lea, Robert N.↗
NASA NTRS1996

A system for the accurate measurement of pointing responses

We present an accurate, yet relatively inexpensive, system for measuring the direction of pointing responses. This system utilizes off-the-shelf business presentation components in a novel way to help detect and quantify the pointing measurements. The system configuration, measurement features, and procedures to enhance measurement accuracy are described.

NASA Center JSC↗
NASA NTRS2009

Power System Mass Analysis for Hydrogen Reduction Oxygen Production on the Lunar Surface

The production of oxygen from the lunar regolith requires both thermal and electrical power in roughly similar proportions. This unique power requirement is unlike most applications on the lunar surface. To efficiently meet these requirements, both solar PV array and solar concentrator systems were evaluated. The mass of various types of photovoltaic and concentrator based systems were calculated to determine the type of power system that provided the highest specific power. These were compared over a range of oxygen production rates. Also a hybrid type power system was also considered. This system utilized a photovoltaic array to produce the electrical power and a concentrator to provide the thermal power. For a single source system the three systems with the highest specific power were a flexible concentrator/Stirling engine system, a rigid concentrator/Stirling engine system and a tracking triple junction solar array system. These systems had specific power values of 43, 34, and 33 W/kg, respectively. The hybrid power system provided much higher specific power values then the single source systems. The best hybrid combinations were the triple junction solar array with the flexible concentrator and the rigid concentrator. These systems had a specific power of 81 and 68 W/kg, respectively.

Colozza, Anthony J.↗
DOE OSTI2021

Case Study: Hybrid Carbon Conversion Using Low-Carbon Energy Sources in Coal-Producing States

The demand for more carbon efficient power sources and a decrease in natural gas prices has decreased the desire for coal power. This decrease in demand has led to massive job losses in coal mining regions over the past decade. The purpose of this project is to develop a hybrid energy system utilizing both a coal power plant and advanced reactor, which is competitive with natural gas by improving on profitability and decreasing carbon emissions. This report details the problem with a summary of the impact on the coal industry and the availability of renewable energy sources in the Appalachian region. Because of the geography of the region, variable renewable energy sources are not available without significant size and siting restrictions. However, biomass in the form of wood waste is abundant and can be used as a carbon neutral energy source. Combining biomass and coal processing, in addition to thermal power plants, can increase system profits and efficiency by providing peaking power and conversion opportunities for secondary markets. The electric load is based on publicly available demand data from Appalachian Power, which services the western Virginia and southern West Virginia in the Appalachian region. The demand information is combined by service, normalized, and scaled to an average demand of 1000 kW, which will be the basis for sizing the hybrid energy system. A traditional screening curve analysis for a coal plant and advanced reactor shows that the least cost design varies significantly based on the assumed discount rate and capital recovery period. An optimization program to size the design in TEAL based on the load curve gives 10 optimal designs, all with a negative resulting net present value (NPV) and a coal plant capacity of less than 15%. Including profits from selling captured carbon at a flat rate results in a positive NPV; however, the coal capacity factor only increases to about 40%. There are limitations with this optimization as well since the price of CO2 is likely to decrease as more is sold to the conversion market. The suggested design will combine coal power, an advanced reactor, and coal and biomass coprocessing to produce a variety of products that can be sold to the conversion market while increasing system efficiency. The analysis of conversion pathways for coal and biomass reveals that multiple options will need to be included in the analysis to produce the optimal system design. Three systems will be optimized and compared to determine the best design based on the figures of merit of total NPV and cost of carbon avoided. The first system will include a coal power plant and an advanced reactor that will sell electricity to the grid to meet demand and sell captured carbon to the conversion market. The second system adds a high-temperature steam electrolysis plant, which will utilize electricity during times of low demand to produce hydrogen and sell it to the conversion market. The third system adds biomass and coal processing with options for hydrocarbon oils, syngas to be produced for the conversion market, and electricity generation to power components within the system or provide peaking power. This analysis will be based on a new approach that combines traditional screening curve methods with a dispatch algorithm that optimizes the system based on the opportunity cost of different production options. The resulting optimization algorithm should provide results with less processing time than HERON’s decision tree method. The results from this analysis will determine an optimal design and reinforce the benefits of coal power when used in a hybrid energy system. The initial results show that the addition of a secondary market for carbon sales could result in a positive NPV and increases the capacity factor of the coal plant as compared to a design with only sales to the electricity market. The addition of more markets and additional coal consumption from biomass coprocessing could increase NPV further, replace carbon in other markets through the sale of biomass-derived hydrocarbons, and demonstrate the value of coal power technology.

01 COAL, LIGNITE, AND PEAT↗
DOE OSTI2025

Particle Swarm Optimization of Dynamic Load Model Parameters in Large Systems

This paper considers two dynamic load models that are widely used in industry to account for induction motor behavior: CMLD and CLOD. These models must be parametrized for the specific utility system in a general way so that they can be used in planning studies and provide a conservative but realistic representation of load behavior. This study considers a measurement-based approach to tuning both models. The load modeling study compares the response of the tuned models to generic candidate models using historical events. This study considers one area-based subsystem to simplify the modeling approach and reduce the number of models required for simulations. Additionally, because dynamic load models often produce similar results for different sets of parameters, a sensitivity study was conducted to assess the parameter impacts on the voltage response. The sensitivity study covers the parameters that are tuned using event measurements. The process to estimate the parameters uses the particle-swarm optimization algorithm. Overall, the performance of the tuned model more accurately captures recovery voltage, delayed recovery, and settling voltage than its predecessor models while not being overly tuned so that it remains general for peak summer conditions.

dynamic load modeling↗
NASA NTRS2010

Autonomous System for Monitoring the Integrity of Composite Fan Housings

A low-cost and reliable system assesses the integrity of composite fan-containment structures. The system utilizes a network of miniature sensors integrated with the structure to scan the entire structural area for any impact events and resulting structural damage, and to monitor degradation due to usage. This system can be used to monitor all types of composite structures on aircraft and spacecraft, as well as automatically monitor in real time the location and extent of damage in the containment structures. This diagnostic information is passed to prognostic modeling that is being developed to utilize the information and provide input on the residual strength of the structure, and maintain a history of structural degradation during usage. The structural health-monitoring system would consist of three major components: (1) sensors and a sensor network, which is permanently bonded onto the structure being monitored; (2) integrated hardware; and (3) software to monitor in-situ the health condition of in-service structures.

Qing, Xinlin P.↗
DOE OSTI2014

Hybrid insulation coordination and optimisation for 1 MV operation of pulsed electron accelerator KALI-30GW

In a multi-gigawatt pulsed power system like KALI-30 GW, insulation coordination is required to achieve high voltages ranging from 0.3 MV to 1 MV. At the same time optimisation of the insulation parameters is required to minimize the inductance of the system, so that nanoseconds output can be achieved. The KALI-30GW pulse power system utilizes a combination of Perspex, delrin, epoxy, transformer oil, nitrogen/SF{sub 6} gas and vacuum insulation at its various stages in compressing DC high voltage to a nanoseconds pulse. This paper describes the operation and performance of the system from 400 kV to 1030 kV output voltage pulse and insulation parameters utilized for obtaining peak 1 MV output. (author)

43 PARTICLE ACCELERATORS↗
DOE OSTI2015

A comparative study on the environmental impact of supermarket refrigeration systems using low GWP refrigerants

Supermarket refrigeration systems have high environmental impact due to their large refrigerant charge and high leak rates. Consequently, the interest in using low GWP refrigerants such as carbon dioxide (CO 2 ) and new refrigerant blends is increasing. In this study, an open-source Life Cycle Climate Performance (LCCP) framework is presented and used to compare the environmental impact of four supermarket refrigeration systems: a transcritical CO 2 booster system, a cascade CO 2 /N-40 system, a combined secondary circuit with central DX N-40/L-40 system, and a baseline multiplex direct expansion system utilizing R-404A and N-40. The study is performed for different climates within the USA using EnergyPlus to simulate the systems' hourly performance. Finally, further analyses are presented such as parametric, sensitivity, and uncertainty analyses to study the impact of different system parameters on the LCCP.

54 ENVIRONMENTAL SCIENCES↗
NASA NTRS1975

Water hyacinths for removal of cadmium and nickel from polluted waters

Removal of cadmium and nickel from static water systems utilizing water hyacinths (Eichhornia crassipes (Mart.) Solms) was investigated. This aquatic plant demonstrated the ability to rapidly remove heavy metals from aqueous systems by root absorption and concentration. Water hyacinths demonstrated the ability to absorb and concentrate up to 0.67 mg of cadmium and 0.50 mg of nickel per gram of dry plant material when exposed for a 24-hour period to waters polluted with from 0.578 to 2.00 ppm of these toxic metals. It is found that one hectare of water hyacinths has the potential of removing 300 g of cadmium or nickel from 240,000 liters of water polluted with these metals during a 24-hour period.

Wolverton, B. C.↗
NASA NTRS1977

Flight prototype CO2 and humidity control system

A regenerable CO2 and humidity control system is presently being developed for potential use on the space shuttle as an alternative to the baseline lithium hydroxide system. The system utilizes a sorbent material (designated HS-C) to adsorb CO2 and water vapor from the cabin atmosphere and desorb the CO2 and water vapor overboard when exposed to a space vacuum. Continuous operation is achieved by utilizing two beds which are alternately cycled between adsorption and desorption. A shuttle vehicle integration study showed that the HS-C system offers substantial weight advantages compared to the baseline shuttle orbiter expendable lithium hydroxide CO2 removal system for extended missions beyond the nominal design of four men for seven days. This study defined a system packaging envelope in the area presently occupied by the LiOH cartridges.

Rudy, K. M.↗