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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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At least 1,081 records · Page 60

A phase model approach for thermostatically controlled load demand response

A significant portion of electricity consumed worldwide is used to power thermostatically controlled loads (TCLs) such as air conditioners, refrigerators, and water heaters. Because the short-term timing of operation of such systems is inconsequential as long as their long-run average power consumption is maintained, they are increasingly used in demand response (DR) programs to balance supply and demand on the power grid. Here, we present an ab initio phase model for general TCLs, and use the concept to develop a continuous oscillator model of a TCL and compute its phase response to changes in temperature and applied power. This yields a simple control system model that can be used to evaluate control policies for modulating the power consumption of aggregated loads with parameter heterogeneity and stochastic drift. We demonstrate this concept by comparing simulations of ensembles of heterogeneous loads using the continuous state model and an established hybrid state model. The developed phase model approach is a novel means of evaluating DR provision using TCLs, and is instrumental in estimating the capacity of ancillary services or DR on different time scales. We further propose a novel phase response based open-loop control policy that effectively modulates the aggregate power of a heterogeneous TCL population while maintaining load diversity and minimizing power overshoots. This is demonstrated by low-error tracking of a regulation signal by filtering it into frequency bands and using TCL sub-ensembles with duty cycles in corresponding ranges. As a result, control policies that can maintain a uniform distribution of power consumption by aggregated heterogeneous loads will enable distribution system management (DSM) approaches that maintain stability as well as power quality, and further allow more integration of renewable energy sources.

24 POWER TRANSMISSION AND DISTRIBUTION↗

Perspectives on AI Architectures and Codesign for Earth System Predictability

Abstract Recently, the U.S. Department of Energy (DOE), Office of Science, Biological and Environmental Research (BER), and Advanced Scientific Computing Research (ASCR) programs organized and held the Artificial Intelligence for Earth System Predictability (AI4ESP) workshop series. From this workshop, a critical conclusion that the DOE BER and ASCR community came to is the requirement to develop a new paradigm for Earth system predictability focused on enabling artificial intelligence (AI) across the field, laboratory, modeling, and analysis activities, called model experimentation (ModEx). BER’s ModEx is an iterative approach that enables process models to generate hypotheses. The developed hypotheses inform field and laboratory efforts to collect measurement and observation data, which are subsequently used to parameterize, drive, and test model (e.g., process based) predictions. A total of 17 technical sessions were held in this AI4ESP workshop series. This paper discusses the topic of the AI Architectures and Codesign session and associated outcomes. The AI Architectures and Codesign session included two invited talks, two plenary discussion panels, and three breakout rooms that covered specific topics, including 1) DOE high-performance computing (HPC) systems, 2) cloud HPC systems, and 3) edge computing and Internet of Things (IoT). We also provide forward-looking ideas and perspectives on potential research in this codesign area that can be achieved by synergies with the other 16 session topics. These ideas include topics such as 1) reimagining codesign, 2) data acquisition to distribution, 3) heterogeneous HPC solutions for integration of AI/ML and other data analytics like uncertainty quantification with Earth system modeling and simulation, and 4) AI-enabled sensor integration into Earth system measurements and observations. Such perspectives are a distinguishing aspect of this paper. Significance Statement This study aims to provide perspectives on AI architectures and codesign approaches for Earth system predictability. Such visionary perspectives are essential because AI-enabled model-data integration has shown promise in improving predictions associated with climate change, perturbations, and extreme events. Our forward-looking ideas guide what is next in codesign to enhance Earth system models, observations, and theory using state-of-the-art and futuristic computational infrastructure.

54 ENVIRONMENTAL SCIENCES↗

Advancements in Multiphysics Microdepletion Analysis of an eVinci TM -like Microreactor Leveraging OpenMC-CRAB Workflow

Nuclear microreactors (MRs) are a class of nuclear reactor technology, characterized by reduced dimensions, modular design, and reduced power output in contrast to conventional Light Water Reactors (LWRs). MRs are proposed for supplying electricity and eventual process heat to remote locations, such as military installations and disaster-affected areas. Current research work sponsored by the US Department of Energy Microreactor Program (MRP) is devoted to the development of novel modeling and simulation tools to better support MR vendors and regulatory bodies. Notably, the NRC is projected to utilize the CRAB multiphysics software driver for executing both design and beyond-design-basis accident analyses. Furthermore, the NRC has been utilizing the MELCOR code to calculate mechanistic source terms during accidents. Since MELCOR relies on isotopic inventory and reactor temperature/power profiles under accident conditions, which theoretically can be derived from CRAB, the goal is to establish a comprehensive CRAB-MELCOR computational framework. Past work was focused on testing and demonstrating CRAB's capability to generate results that can be used to inform mechanistic source term calculations in MELCOR. In particular, a computational workflow leveraging OpenMC-generated microscopic cross sections and CRAB was first applied to perform multiphysics microscopic depletion calculation followed by an accident scenario for a stylized microreactor problem. In fiscal year 2024, the research work has been focused on applying the OpenMC-CRAB workflow, which was first tested in fiscal year 2023, to a realistic 3D heat-pipe cooled MR problem representative of the eVinci TM design. The latter computational problem was developed with inputs from WEC to conserve selected neutronic and thermal characteristics of the eVinci TM design without releasing proprietary data. The results of this simulation, encompassing isotopic inventory, power density distribution, and kinetic parameters, will inform both MELCOR and the WEC-developed FATE code for mechanistic source terms calculations. The results from the two codes will then be compared for code verification purposes. This report contains the design characteristics of the realist heat pipe cooled microreactor developed as a use-case for the verification exercise, and the current results for the multiphysics microscopic depletion performed with the OpenMC-CRAB workflow. The results include eigenvalue as a function of time, power distribution at EOL, in addition to nuclides inventory's time evolution and spatial distribution. Finally, we report improvements to the workflow efficiency achieved through a collaboration with the NEAMS programs. Through this collaborative effort, we were able to strongly decrease the computational time for the multiphysics microdepletion calculation (i.e., from 17.4 hours to 5.7 hours on 280 processors) in addition to simplifying the interface to generate isotopics spatial distribution utilizable by FATE and MELCOR. Future work, including the improvement of the current microscopic cross-sections' library and the simulation of an accident scenario at EOL, is also discussed.

22 GENERAL STUDIES OF NUCLEAR REACTORS↗

Perspectives on AI Architectures and Co-design for Earth System Predictability

Recently, the U.S. Department of Energy (DOE), Office of Science, Biological and Environmental Research (BER), and Advanced Scientific Computing Research (ASCR) programs organized and held the Artificial Intelligence for Earth System Predictability (AI4ESP) workshop series. From this workshop, a critical conclusion that the DOE BER and ASCR community came to is the requirement to develop a new paradigm for Earth system predictability focused on enabling artificial intelligence (AI) across the field, laboratory, modeling, and analysis activities, called model experimentation (ModEx). BER’s ModEx is an iterative approach that enables process models to generate hypotheses. The developed hypotheses inform field and laboratory efforts to collect measurement and observation data, which are subsequently used to parameterize, drive, and test model (e.g., process based) predictions. A total of 17 technical sessions were held in this AI4ESP workshop series. This paper discusses the topic of the AI Architectures and Codesign session and associated outcomes. The AI Architectures and Codesign session included two invited talks, two plenary discussion panels, and three breakout rooms that covered specific topics, including 1) DOE high-performance computing (HPC) systems, 2) cloud HPC systems, and 3) edge computing and Internet of Things (IoT). We also provide forward-looking ideas and perspectives on potential research in this codesign area that can be achieved by synergies with the other 16 session topics. These ideas include topics such as 1) reimagining codesign, 2) data acquisition to distribution, 3) heterogeneous HPC solutions for integration of AI/ML and other data analytics like uncertainty quantification with Earth system modeling and simulation, and 4) AI-enabled sensor integration into Earth system measurements and observations. Such perspectives are a distinguishing aspect of this paper.

58 GEOSCIENCES↗

Recent Developments at the Raft River Geothermal Field

The Raft River geothermal field, located in Cassia County in southwestern Idaho, is the site of a Department of Energy Enhanced Geothermal System project. U.S. Geothermal, Inc. currently produces about 11 MWe from Precambrian metamorphic rocks. These lie beneath ~5,000 ft of Quaternary and Tertiary volcaniclastic and volcanic deposits. Maximum temperatures range from 271°F to 300°F. Well RRG-9 ST1, the well targeted for stimulation is located approximately 1 mile south of the main bore field. The open hole section of the well, from 5,551 to 5,900 ft MD, consists of Precambrian Elba Quartzite, the stimulation target, granite and minor diabase. Prior to setting the casing acoustic, gamma ray, and density logs were run. After completing the well, a step rate/step down test was conducted. The maximum injection rate achieved was 18 bpm at a wellhead pressure of 1,150 psig. A borehole televiewer run in the open hole section showed evidence of more than eighty fractures. The majority of these fractures trend from N20⁰W to N20°E and dip from 40° to 60°W. Permeable fractures were encountered in the Elba Quartzite at 5,640-5,660 ft MD. Analysis of the injection test indicates that the minimum in-situ principal stress in this zone is 3,050-3,200 psi, corresponding to a fracture gradient of 0.59-0.62 psi/ft. A discrete fracture network model was developed using measured and inferred fracture orientations, distributions and dimensions. A three-phase stimulation program is proposed for RRG-9 ST-1. During the first two stages, water at 140°F, and later 40°F, will be injected to pre-condition and thermally fracture the reservoir. Here, the third stage will consist of a high rate, large volume conventional hydraulic stimulation.

Bradford, Jacob↗

Rolling Optimization of Transmission Network Recovery and Load Restoration Considering Hybrid Wind-Storage System and Cold Load Pickup

A common solution to deal with the stochasticity introduced by fast-ramping wind power integration is to equip wind farms (WFs) with energy storage systems (ESSs) to formulate hybrid WF-ESSs. In addition to leveling off wind power fluctuations during normal operations, a hybrid WF-ESS can be a flexible power source to accumulate the power system restoration. In this paper, we propose a rolling optimization model for transmission network recovery and load restoration considering the contributions of WF-ESSs. The proposed model is formulated as a mixed integer linear programming problem that simultaneously optimizes the amount and location of restorable load blocks as well as the restoration lines. The cold load pickup features of interrupted loads considering the outage duration are modeled in detail. A chance-constrained method is employed to deal with the uncertainty of wind power, and a rolling horizon-based framework is adopted to reduce the influence of forecast error. Case studies are conducted on both New England 39-bus system and part of a provincial power system in China. The results show that the load restoration process can be significantly accelerated by employing the proposed method and contributions of hybrid WF-ESSs to power system restoration are validated.

chance-constrained optimization↗

Innovative Pathways: Transforming Impact Investments to Working Capital For Early Stage Cleantech Companies: Los Angeles Cleantech Incubator (January 1, 2020 to March 31, 2020)

Project Objectives: The focus for the entirety of the last quarter was on the completion of the pilot loan funding within our portfolio, and the closing out of our DOE-CAP Grant: “Innovative Pathways: Transforming Impact Investments to Working Capital for Early Stage Cleantech Companies.” The fourteenth quarter (Q14) of the program performance was also dedicated toward two main activities: the continued fundraising efforts for a formalized LACI debt fund, as well as finalization of the lending processes for pilot underwriting amongst the LACI Team and with Mission Driven Finance. This quarter marked key successes around the workflows of the DOE-CAP grant, specifically around fund capitalization efforts. Activities during the thirteenth quarter included: 1. Finalization of the DOE-CAP grant activities and work-flows; 2. Due diligence, underwriting and issuance of one (1) loan in Q1 2021 and three (3) in Q4 2020 for technology providers in grant-funded zero emissions mobility & community pilots, in partnership with LACI and local organizations, totaling ten (10) total loans; 3. Development of fundraising and marketing materials, and distribution to 30+ possible funding sources over the course of Q13 & Q14; and 4. Reinvigoration of conversations with Mission Driven Finance, the prospective underwriting partner for key activities and governance documents, and finalization of all loan processing activities once the fund is capitalized

29 ENERGY PLANNING, POLICY, AND ECONOMY↗

Modeling the Interaction Between Energy Efficiency and Demand Response on Regional Grid Scales: Preprint

With increasing penetration of intermittent renewable generation at grid and distributed scales, flexible building loads can provide significant system value and support the evolving needs of the grid. The growing value of load flexibility may complicate the traditional separation between energy efficiency (EE) and demand response (DR). EE measures may compete in some cases with a building’s DR capabilities but complement one another in other cases. EE can also increase or decrease the need for DR at the system level and change the availability of DR to meet system needs. In this study we present a bottom-up approach to modeling interactive effects between EE and DR in buildings within two regions of the US electricity grid. From a library of building simulation models for different buildings and climates, we synthesize system-level demand profiles and the impacts of potential future EE portfolios. Coupling the underlying building models with a database of DR-enabling technologies, we then compute the quantity of DR that can be delivered in each scenario. The results show that EE and DR interactions are largely driven by the timing of EE savings that are measure-specific and the coincidence with system peak demand that is region-specific. We also find that perspective of the impacts matters – for instance that some EE measures reduce the system need for DR but also reduce the DR potential. Our results imply that utility EE and DR programs developed without considering interactive effects may lead to increased grid-management challenges over the long term.

buildings↗

Reconstructing Solar Particle Event Spectra from Absorbed Dose Measurements

The space radiation environment is unlike anything encountered on Earth. It is dominated by heavy charged particles consisting of highly charged nuclei with atomic numbers ranging from 1 to 94 with a broad spectrum of kinetic energies. The three primary sources of radiation in space are trapped belts, galactic cosmic rays (GCRs), and solar particle events (SPEs). The trapped belts are only of concern near bodies with significant magnetic fields and GCR flux spectra are relatively well-predicted using models that account for solar modulation of the local interstellar spectrum. SPEs, which consist primarily of protons, are difficult to predict in terms of occurrence, duration, intensity, and energy spectrum. SPE intensity and energy spectrum are critical for understanding radiation exposure-related health effects for astronauts in space. The National Aeronautics and Space Administration (NASA) relies on data from the Geostationary Operational Environmental Satellite series to characterize intensities and energy spectra of SPEs near Earth. However, these data are not applicable for spacecraft in other regions of the solar system. To understand the radiation environment for astronauts embarking on travel beyond Earth orbit, NASA is developing the Hybrid Electronic Radiation Assessor (HERA), a distributed dosimetry system that employs a solid-state silicon sensor coupled with the Timepix readout chip. The pixelated nature of the detector permits detailed analyses of charged particle tracks which can then be used to characterize the fluence spectrum at the location of the detector. Despite the unprecedented level of detail regarding the radiation environment provided by these detectors, knowledge of the fluence spectrum at all locations within the vehicle, specifically inside of astronauts, is desired to fully characterize the associated risk of harmful health effects. Radiation transport of the external radiation environment, considering the shielding provided by the vehicle, other objects, and even astronauts, is performed to obtain this information. Thus, there is clearly a need to define the external radiation environment using measurements performed within the vehicle. The number of detectors that may be flown as a part of HERA is limited by logistics, including data, power, and mass restrictions. The current configuration for crewed flight consists of six detectors at various locations with in the Orion Multi-Purpose Crew Vehicle (MPCV). It follows that an external proton fluence spectrum can be characterized with at most six energy bins with traditional matrix inversion techniques. The purpose of the present study is to determine whether it is possible to reconstruct SPE spectra with greater resolution from absorbed dose measurements and knowledge of the response of individual detectors using linear programming.

46 INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AND ↗

A New Fast Fluid Dynamics Model for Data-Center Floor Plenums

A raised-floor plenum is often used to distribute cooling airflow in data centers. Traditional Computational Fluid Dynamics (CFD) can accurately model airflow distribution in plenums, but it is expensive (computationally and financially) and is, therefore, often not accessible to the data center designer or operator. This paper presents an alternative CFD methodology based on Fast Fluid Dynamics (FFD), which is faster, more parallelizable, and simpler to program. The improvement in computational speed afforded by FFD is particularly important for multiple-iteration optimization, transient simulations, or applications for which near-real-time performance is required. Here, the potential speed improvements of FFD have been widely documented; however, it has been generally accepted that this benefit is accompanied by a modest loss of accuracy relative to traditional CFD. We show here that this is not necessarily true. Plenum airflow predictions by our FFD implementation, which utilizes a first-order upwind rather than Semi-Lagrangian advection scheme of previous research, are extremely close to those predicted by traditional CFD - provided the same turbulence model and computational grid are used consistently.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗

Hierarchical Model-Free Transactional Control of Building Loads to Support Grid Services

A transition from generation on demand to consumption on demand is one of the solutions to overcome the many limitations associated with the higher penetration of renewable energy sources. Such a transition, however, requires a considerable amount of load flexibility in the demand side. Demand response (DR) programs can reveal and utilize this demand flexibility by enabling the participation of a large number of grid-interactive efficient buildings (GEB). Existing approaches on DR require significant modelling or training efforts, are computationally expensive, and do not guarantee the satisfaction of end users. To address the aforementioned limitations, this software code considers a scalable hierarchical model-free transactional control approach that incorporates elements of virtual battery, game theory, and model-free control (MFC) mechanisms. The developed approach separates the control mechanism into upper and lower levels. The MFC modulates the flexible GEB in the lower level with guaranteed thermal comfort of end users in response to the optimal pricing and power signals determined in the upper layer using a Stackelberg game integrated with aggregate virtual battery constraints. Additionally, the usage of MFC necessitates less burdensome computational and communication requirements, thus, it is easily deployable even on small, embedded devices. This software code enables the use of residential and small-size commercial buildings to offer a potentially substantial source of ancillary grid services that are currently underutilized. A hierarchical, model-free transactive building control provides a smooth interface between the grid service requests of utilities and the reliable control required by participating buildings. Model-free control, which supports distributed control architecture, will be a more scalable solution that can be deployed in neighborhood-size systems as well as individual buildings. The proposed approach contributes to the body of knowledge on two main aspects. First, it couples the MFC with the game-theoretic control and proposes a scalable model-free transactive control approach. MFC does not require any modeling effort or model training for the various building loads. This is very beneficial since deriving an accurate model for every single unit participating in DR programs and obtaining all the parameters about the units (e.g., thermal coefficients, standby losses) are infeasible. Also, MFC is computationally efficient, easily deployable even on small, embedded devices, and can be implemented in real time. Second, it integrates the concept of virtual battery into DR via the Stackelberg game. The concept of virtual battery enables efficient coordination and aggregation of a large number of flexible GEB with guaranteed thermal comfort of end users.

Olama, Mohammed [Oak Ridge National Lab. (ORNL), O↗

Geochemical characterization of floodplain sediments from Meander C and O in the East River Watershed, CO, USA

This data package is part of the Watershed Function SFA data collection and contains geochemical characterization of sediments as a function of depth in the pumphouse vicinity, including Meander C and Meander O (oxbow). This data was used in the manuscript "Fox, P.M., Bill, M., Heckman, K., Conrad, M., Anderson, C., Keiluweit, M., and Nico, P.S.Shale as a Source of Organic Carbon in Floodplain Sediments of a Mountainous Watershed" published in Journal of Geophysical Research: Biogeosciences. Data includes sieving, total organic carbon (TOC), total inorganic carbon (TIC), total nitrogen (TN), carbon isotopes (14C and 13C) of whole sediment. Sediment density fractionation data is also included, with measurements of TOC, TN, 14C and 13C on density fractions. Metal and carbon concentrations from various sediment extractions (HCl, dithionite, oxalate, water, and pyrophosphate) are included. Characterization of extracted carbon by fourier transform infrared spectroscopy (FTIR) and UV-Visible light spectroscopy. Characterization of density fractionated (light fractions) organic carbon by FTIR. Carbon X-ray spectroscopy (C near edge X-ray absorption fine structure spectroscopy [NEXAFS] and scanning transmission X-ray microscopy [STXM]) is also included for shale samples and sediment samples.Additional acknowledgements:1. M.K. and C.A. were supported by the Department of Energy, Office of Biological and Environmental Research, Subsurface Biosphere Research program (award no. DE-SC0016544).2. STXM and NEXAFS data was collected at the Canadian Light Source, which is supported by the Canada Foundation for Innovation, Natural Sciences and Engineering Research Council of Canada, the University of Saskatchewan, the Government of Saskatchewan, Western Economic Diversification Canada, the National Research Council Canada, and the Canadian Institutes of Health Research.3. Radiocarbon analysis was supported in part by the Radiocarbon Collaborative, which is jointly sponsored by the USDA Forest Service Northern Research Station, the KCCAMS Facility at UC Irvine, and Michigan Technological University.Update 11/06/2019: An .kml file was added with the GPS locations for all the sampling sites.

54 ENVIRONMENTAL SCIENCES↗

Collab Fracture Characterization: Preliminary Results from the Modeling and Flow Testing of Experiment 1

The EGS Collab project is developing ~10-20 m-scale field sites where fracture stimulation and flow models can be validated against controlled, small-scale, in-situ experiments. At the first experimental site, a hydraulic fracture will be created in metamorphic rock at the 4850 level in the former Homestake Mine. The experimental concept is for fracturing to be initiated at an injection well and continue until it intersects a production well approximately 10 meters away. Initial step-pressure flow testing of the fracture are to be performed to describe pressure-aperture-flow relationships. The flow field between the injector and producer boreholes will be characterized using a series of forced gradient dipole tracer tests. A number of fracture characterization models have been used to assist in the design of the tracer tests. The tracer test program will use conservative, sorbing, and particulate tracers, as well as sampling for radon gas to describe the fracture surface area (i.e., potential heat transfer area), flow pathway distribution, and volume. Tracer concentration at the production well (i.e. break through curves) will be measured using a series of inline sensors, liquid sampling devices, filtering of the effluent, and the measuring of gas concentrations in the effluent. Tracer monitoring data will be compared against results from a collection of numerical simulators developed at U.S. national laboratories and universities for the purpose of validating these flow and transport models. Ultimately these same models will be used to predict the heat transfer characteristics of the fracture and will be compared to a thermal characterization field test where cold water will be injected at the injection well and the temperature will be measured at the production well. This paper discusses the early tracer transport model predictions and parameters sensitivity that affect the tracer breakthrough curves at the production well.

15 GEOTHERMAL ENERGY↗

Collab Fracture Characterization: Preliminary Results from the Modeling and Flow Testing of Experiment 1

The EGS Collab project is developing ~10-20 m-scale field sites where fracture stimulation and flow models can be validated against controlled, small-scale, in-situ experiments. At the first experimental site, a hydraulic fracture will be created in metamorphic rock at the 4850 level in the former Homestake Mine. The experimental concept is for fracturing to be initiated at an injection well and continue until it intersects a production well approximately 10 meters away. Initial step-pressure flow testing of the fracture are to be performed to describe pressure-aperture-flow relationships. The flow field between the injector and producer boreholes will be characterized using a series of forced gradient dipole tracer tests. A number of fracture characterization models have been used to assist in the design of the tracer tests. The tracer test program will use conservative, sorbing, and particulate tracers, as well as sampling for radon gas to describe the fracture surface area (i.e., potential heat transfer area), flow pathway distribution, and volume. Tracer concentration at the production well (i.e. break through curves) will be measured using a series of inline sensors, liquid sampling devices, filtering of the effluent, and the measuring of gas concentrations in the effluent. Tracer monitoring data will be compared against results from a collection of numerical simulators developed at U.S. national laboratories and universities for the purpose of validating these flow and transport models. Ultimately these same models will be used to predict the heat transfer characteristics of the fracture and will be compared to a thermal characterization field test where cold water will be injected at the injection well and the temperature will be measured at the production well. This paper discusses the early tracer transport model predictions and parameters sensitivity that affect the tracer breakthrough curves at the production well.

15 GEOTHERMAL ENERGY↗

A Review of the Generic Grid-Forming Model Used by the System Operator in Chile

The objective in this project is to verify the applicability of using generic electro-magnetic transient domain models of GFM technology through a wide range of tests and system conditions proposed by subject matter experts of GFM technology through a wide range of tests and system conditions proposed by subject matter experts. For this study, we used the generic GFM electro-magnetic transient model available in the EMTP (Electromagnetic Transient Program) software library, and we assessed the model’s various GFM capabilities through 12 tests. In this report, we compare the performance of the model with that of an original equipment manufacturer (OEM) GFM model. We also share the key insights and lessons learned from this work.

24 POWER TRANSMISSION AND DISTRIBUTION↗

Many-body Nuclear Dynamics

The principal goal of this work was to better understand the fusion of neutron-rich nuclei a topic relevant to the fields of both nuclear physics and nuclear astrophysics. The work provides insight into the structure and reactions of neutron-rich nuclei namely the extent of their neutron density distribution and its polarizability. By comparing the fusion excitation functions for a chain of isotopes with a common target nucleus changes in the attractive nuclear potential are assessed. This change in the attractive potential is related to changes in the neutron density distribution with increasing number of neutrons or changes in fusion dynamics with increasing neutron number. The impact of the pairing of valence neutrons and protons on the fusion cross-section is also examined. Measurement of an isotopic chain is a powerful tool to address this topic. The experimental program made use of several different accelerator facilities. The core of the experimental work involved experiments at the ReA3 accelerator and the Facility for Rare Isotope Beams (FRIB) situated at Michigan State University, at GANIL, the French national nuclear physics laboratory, and the University of Notre Dame. At ReA3 the degree to which α-clusters associated with fusion of 28,30,32 Si + 28 Si result from the collision dynamics or reflect an initial α-cluster structure was explored. Alpha clusters observed in fusion reactions exceed the predictions of the standard statistical model. This experiment provides a measure of how clusterization is impacted by the increasing neutron-richess of the system. In the experiment at GANIL we investigated fusion in 19 O + 12 C and 20 O + 12 C. This experiment utilized the recently developed active-target detector MuSIC@Indiana. Using this proven, highly efficient, active-target detector we measured the fusion excitation function for these neutron-rich systems. Grounded by these experimental measurements, theoretical models were used to examine the role of unpaired valence neutrons on the fusion cross-section at energies just above the fusion barrier.

73 NUCLEAR PHYSICS AND RADIATION PHYSICS↗

Advanced control techniques for modern inertia based inverters

In this research three artificial intelligent (AI)-based techniques are proposed to regulate the voltage and frequency of a grid-connected inverter. The increase in the penetration of renewable energy sources (RESs) into the power grid has led to the increase in the penetration of fast-responding inertia-less power converters. The increase in the penetration of these power electronics converters changes the nature of the conventional grid, in which the existing kinetic inertia in the rotating parts of the enormous generators plays a vital role. The concept of virtual inertia control scheme is proposed to make the behavior of grid connected inverters more similar to the synchronous generators, by mimicking the mechanical behavior of a synchronous generator. Conventional control techniques lack to perform optimally in nonlinear, uncertain, inaccurate power grids. Besides, the decoupled control assumption in conventional VSGs makes them nonoptimal in resistive grids. The neural network predictive controller, the heuristic dynamic programming, and the dual heuristic dynamic programming techniques are presented in this research to overcome the draw backs of conventional VSGs. The nonlinear characteristics of neural networks, and the online training enable the proposed methods to perform as robust and optimal controllers. The simulation and the experimental laboratory prototype results are provided to demonstrate the effectiveness of the proposed techniques.

24 POWER TRANSMISSION AND DISTRIBUTION↗

Regime-specific Cloud Vertical Overlap Characteristics from Radar and Lidar Observations at the ARM sites

Climate and numerical weather prediction models require assumptions to represent the vertical distribution of subgrid-scale clouds, which have radiative transfer implications. In this study, nearly 25 years of ground-based radar and lidar observations of vertical cloud profiles at the Atmospheric Radiation Measurement Program (ARM) Southern Great Plains (SGP) site are utilized to derive cloud vertical overlap characteristics from the Cloud Type (CLDTYPE) data product. Here, the cloud vertical overlap characteristics are further separated by cloud regime by considering seven cloud types (i.e., low cloud, congestus, deep convection, altocumulus, altostratus, cirrostratus, and cirrus) as well as periods of shallow cumulus. The decorrelation length scale (i.e., exponential transition from maximum to random overlap with layer separation) is found to vary by cloud regime, ranging between 0.04 km for cirrostratus paired with cirrus to 4.58 km for low cloud paired with cirrus at SGP. Cloud vertical overlap characteristics are also considered for other ARM sites including the Tropical Western Pacific (TWP), North Slope of Alaska (NSA), and Eastern North Atlantic (ENA) sites amongst other shorter term ARM deployments globally. The decorrelation length scale ranged globally from 1.03 km in the Arctic Ocean to 3.06 km in Manacapuru, Brazil. Globally, the decorrelation length scale by cloud regime exhibited similarities (e.g., for cirrus paired with cirrus) and differences (e.g., congestus paired with cirrus). The results could help inform development of cloud vertical overlap assumptions within operational numerical weather prediction models and potentially improve prediction of radiative fluxes for weather, climate, and renewable energy forecasting.

54 ENVIRONMENTAL SCIENCES↗