Search NASA⌕ Search

SEARCH · Search NASA

Results for “Distributed Energy Program”

Search indexed NASA NTRS and DOE OSTI research on propulsion, heat transfer, battery materials and energy systems. Follow report and document links to the original sources.

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

At least 1,477 records · Page 82
All sourcesNASA NTRSDOE OSTI
DOE OSTI2024

Nucleon Structure Studies at Jefferson Lab and the Electron Ion Collider

The research programs of Thomas Jefferson Laboratory (JLab) and the future Electron- Ion Collider (EIC) focus on one of the main goals of strong interaction studies : understanding the structure of nucleons in terms of the quarks and gluons composing them. Their structure is encoded in functions such as Generalized Parton Distributions (GPDs), which describe how quarks and gluons’ transverse position and longitudinal momentum are distributed inside nucleons. GPDs allow to obtain three-dimensional pictures of nucleons and to understand some of their fundamental properties, such as their internal pressure or the emergence of their spin from the dynamics of the partons composing them. At JLab and the EIC, electron beams are used to probe nucleons. Measurement of reactions such as Deeply Virtual Compton Scattering (DVCS) allows access to GPDs. The first longitudinally polarized-target experiment of the CLAS12 program at Jlab took place in 2022-2023. Combining polarized electron beams and nucleon targets, this experiment offers unique access to observables that allow the measurement of different types of GPDs. In particular, the DVCS beam- and target-spin asymmetries for protons and neutrons in deuterium will be measured for the first time. They give access to kinds of GPDs that are still poorly known, and the comparison between proton and neutron data will allow the extraction of the flavor dependence of the structure of nucleons. Specific analysis methods have been implemented to work with a polarized nuclear target and are presented in this thesis. These methods allow to obtain preliminary results for the asymmetries, waiting for the complete statistics to be available. In the long term, the experimental program for the EIC has been established with a strong emphasis on the measurement of the structure of nucleons at high energy. Measurements of reactions such as DVCS impose strict requirements on the electromagnetic calorimeter that will allow to measure the energy of the scattered electrons and photons. This calorimeter, which is under development, will be based on scintillating crystals read by Silicon Photomultipliers (SiPMs). A new type of glass-based scintillating material was tested, evaluating the possibilities to meet the technical requirements concerning their light yield and resistance to radiation damage in particular. Several models of SiPMs have been characterized, demonstrating they can operate over the vast energy range necessary to address the physics case at the EIC and providing guidelines for developing their readout electronics.

Pilleux, Noemie↗
DOE OSTI2021

AI-based design of a nuclear reactor core

The authors developed an artificial intelligence (AI)-based algorithm for the design and optimization of a nuclear reactor core based on a flexible geometry and demonstrated a 3× improvement in the selected performance metric: temperature peaking factor. The rapid development of advanced, and specifically, additive manufacturing (3-D printing) and its introduction into advanced nuclear core design through the Transformational Challenge Reactor program have presented the opportunity to explore the arbitrary geometry design of nuclear-heated structures. The primary challenge is that the arbitrary geometry design space is vast and requires the computational evaluation of many candidate designs, and the multiphysics simulation of nuclear systems is very time-intensive. Therefore, the authors developed a machine learning-based multiphysics emulator and evaluated thousands of candidate geometries on Summit, Oak Ridge National Laboratory’s leadership class supercomputer. The results presented in this work demonstrate temperature distribution smoothing in a nuclear reactor core through the manipulation of the geometry, which is traditionally achieved in light water reactors through variable assembly loading in the axial direction and fuel shuffling during refueling in the radial direction. The conclusions discuss the future implications for nuclear systems design with arbitrary geometry and the potential for AI-based autonomous design algorithms.

22 GENERAL STUDIES OF NUCLEAR REACTORS↗
NASA NTRSDate not supplied

Numerical Investigation of Combustor-Turbine Interactions with a Two-Stage High-Pressure Turbine Including Cooling Airflows

Combustor–turbine interactions (CTIs) are investigated by performing three-dimensional unsteady simulations using a realistic combustor and high-pressure turbine (HPT) configurations from the Energy Efficient Engine (E3) program. To understand CTIs, we compare the numerically predicted flow fields from single-component simulations (Step 1: the combustor + the first-stage stator of turbine; Step 2: the two-stage HPT imposing the time-averaged flow solution from Step 1 as the inflow boundary condition) and a fully coupled combustor–turbine simulation (Step 3) at the sea-level takeoff (SLTO) condition. In addition to three previous simulations where the cooling airflows inside the HPT had been neglected for all Step 1, Step 2, and Step 3, two new simulations of Step 2 and Step 3 take into account the cooling airflows using the source team approach. In this approach, to mimic the cooling airflows, we impose the source term at a specific area of a cooling airflow hole at the solid surfaces without making a mesh of each hole. The objective of this study is twofold. One is to investigate the effect of the presence of the cooling airflows on the aerodynamics of the combustor and HPT as well as the HPT performance. The second is to perform a detailed comparison among the calculated flowfields by two different numerical schemes, the central-difference with the standard Jameson–Schmidt–Turkel (CD-JST) scheme and the AUSM scheme. There is a noticeable difference in the hot-streak distributions at the first-stage stator. In addition, depending on the choice of the numerical scheme and the presence of the cooling airflows, an occurrence of shock waves appearing at the first-stage stator is greatly influenced. Thus, this has a noticeable impact on the HPT performance. It is shown that the estimated turbine efficiencies from Step 3 are about 7 % less than the ones from Step 2.

Combustor-turbine interaction↗
DOE OSTI2025

Study of deeply virtual Compton scattering at the future electron-ion collider

This study presents the impact of future measurements of deeply virtual Compton scattering (DVCS) with the ePIC detector at the electron-ion collider (EIC), currently under construction at Brookhaven National Laboratory. The considered process is sensitive to generalized parton distributions (GPDs), the understanding of which is a cornerstone of the EIC physics program. Our study marks a milestone in the preparation of DVCS measurements at EIC and provides a reference point for future analyses. In addition to presenting distributions of basic kinematic variables obtained with the latest ePIC design and simulation software, we examine the impact of future measurements on the understanding of nucleon tomography and DVCS Compton form factors, which are directly linked to GPDs. We also assess the impact of radiative corrections and background contribution arising from exclusive π 0 production.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗
NASA NTRS2003

Vertically Resolved Aerosol Optical Properties over the ARM SGP Site

In order to meet one of its goals - to relate observations of radiative fluxes and radiances to the atmospheric composition - the Department of Energy's Atmospheric Radiation Measurement (ARM) program has pursued measurements and modeling activities that attempt to determine how aerosols impact atmospheric radiative transfer, both directly and indirectly. However, significant discrepancies between aerosol properties measured in situ or remotely remain. To this end, the ARM program will conduct an Aerosol Intensive Operational Period (IOP) in May 2003 at the ARM Southern Great Plains (SGP) site in north central Oklahoma. The IOP involves airborne measurements from two airplanes over the heavily instrumented SGP site. We will give an overview of early airborne results obtained aboard Center for Interdisciplinary Remotely-Piloted Aircraft Studies (CIRPAS) Twin Otter aircraft. The aircraft will carry instrumentation to perform in-situ measurements of aerosol absorption, scattering, extinction and particle size including such novel techniques as the photoacoustic and cavity ring-down methods. Aerosol optical depth and extinction will be measured with the NASA Ames Airborne Tracking 14-channel sunphotometer. Furthermore up- and downwelling solar (broadband and spectral) and infrared radiation will be measured using three different instruments. The up-looking radiation instruments will be mounted on a newly developed stabilized platform, which will keep the instruments level up to aircraft pitch and roll angles of 10 degrees. Additional effort will be directed toward measurement of cloud condensation nucleus concentration as a function of supersaturation and relating CCN concentration to aerosol composition and size distribution. This relation is central to description of the aerosol indirect effect.

Schmid, B.↗
DOE OSTI2017

Holistic Interactions of Shallow Clouds, Aerosols, and Land-Ecosystems (HI-SCALE) Field Campaign Report

Cumulus convection is an important component in the atmospheric radiation budget and hydrologic cycle over the southern Great Plains and over many regions of the world, particularly during the summertime growing season when intense turbulence induced by surface radiation couples the land surface to clouds. Current convective cloud parameterizations contain uncertainties resulting in part from insufficient coincident data that couples cloud macrophysical and microphysical properties to inhomogeneities in land surface, boundary layer, and aerosol properties. The Holistic Interactions of Shallow Clouds, Aerosols, and Land-Ecosystems (HI-SCALE) campaign was designed to provide a detailed set of measurements that are needed to obtain a more complete understanding of the lifecycle of shallow clouds by coupling cloud macrophysical and microphysical properties to land surface properties, ecosystems, and aerosols. Some of the land-atmosphere-cloud interactions that can be studied using HI-SCALE data are shown in Figure 1. HI-SCALE consisted of two 4-week intensive operation periods (IOPs), one in the spring (April 24-May 21) and the other in the late summer (August 28-September 24) of 2016, to take advantage of different stages of the plant lifecycle, the distribution of “greenness” for various types of vegetation in the vicinity of the U.S. Department of Energy (DOE) Atmospheric Radiation Measurement (ARM) Climate Research Facility Southern Great Plains (SGP) site, and aerosol properties that vary during the growing season. As expected, satellite measurements indicated that the Normalized Difference Vegetation Index (NDVI) was much “greener” in the vicinity of the SGP site during the spring IOP than the late summer IOP as a result of winter wheat maturing in the spring and being harvested in the early summer. As shown in Figure 2, temperatures were cooler than average and soil moisture was high during the spring IOP, while temperatures were warmer than average and soil moisture was low during the late summer IOP. These factors likely influence the occurrence and lifecycle of shallow clouds. Most of the instrumentation was deployed on the ARM Aerial Facility (AAF) Gulfstream 1 (G-1) aircraft, including those that measure atmospheric turbulence, cloud water content and drop size distributions, aerosol precursor gases, aerosol chemical composition and size distributions, and cloud condensation nuclei (CCN) concentrations. The specific instrumentation is listed in Table 1. The team of scientists participating in the G-1 flights were from Pacific Northwest National Laboratory (PNNL), Brookhaven National Laboratory (BNL), and the University of Washington. Routine ARM aerosol measurements made at the surface were supplemented with aerosol microphysical properties measurements, with support from the DOE Environmental Molecular Sciences Laboratory (EMSL) User Facility and the Atmospheric System Radiation (ASR) program. This included deploying a scanning mobility particle sizer (SMPS) to measure aerosol size distribution, a proton transfer reaction-mass spectrometer (PTR-MS) to measure volatile organic compounds, an aerosol mass spectrometer (AMS) to measure bulk aerosol composition, and the single-particle laser ablation time-of-flight mass spectrometer (SPLAT II) to measure single-particle aerosol composition at the SGP site Guest Instrumentation Facility. In this way, characterization of aerosol properties at the surface and on the G-1 were consistent. In addition, the HI-SCALE: Nanoparticle Composition and Precursors add-on campaign was conducted during the second IOP in which several state-of-the-science chemical ionization mass spectrometers were deployed to measure nanoparticle composition and precursors. Scientists participating in the surface measurements were from PNNL, BNL, University California–Irvine, Augsberg College, Colorado University, Aerodyne Inc., and Aerosol Dynamics Inc.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2019

A BI-LEVEL APPROACH TO FUTURE POWER SYSTEM CO-OPTIMIZATION WITH HIGH PENETRATION OF RENEWABLE ENERGY AND RESPONSIVE DEMAND

Electricity generation accounts for nearly half of the total CO2 emissions in the United States. For this reason, the development and integration of renewable resources will play an essential role in achieving the societal objective of mitigating climate change through reduction of greenhouse gas emissions. In conjunction with the environmental benefits of renewable energy, the most common renewable sources, such as wind and solar, also increase the uncertainties surrounding generation in power systems, which adds significant challenges to the system operation and planning. The uncertainties and forecasting errors surrounding renewable generation are normally addressed through the use of reserves from traditional generators. At greater levels of renewable penetration, sufficient generator reserves may not be available or economically viable. In contrast, the promise of demand-side resources in this arena lies in the spatially widespread availability, rapid response potential, and lower cost of features that already exist in the system. However, the challenge of responsive demand arises from the need to understand, manage, and incentivize a very large number of resources to participate effectively in efficient operation of the complex power system. Since demand response comes from the distribution system, microgrids as the basic building blocks of future distribution systems will be a critical environment for the study of demand response. To support integration of microgrids with flexible loads in future power systems, the operational mode of power systems will need to evolve. Therefore, it is going to be critical to have new and efficient co-optimization methods for coordination of the various power market participants and the scheduling of resources in the power systems of the future. Motivated by the rapid increase in renewable penetration, the need for effective demand response programs, and a changing system structure, this dissertation seeks to define a new strategy that supports co-optimization of various participants in power systems with emphasis on high renewable penetration and demand response. This strategy has three components; 1) an exploration of the capabilities of different types of demand response programs in a microgrid, 2) development and implementation of a bi-level framework for co-optimization of the main grid with high renewable penetration and a microgrid with demand response capabilities, and 3) expansion of the bi-level framework from a microgrid to a general distribution system to explore the advantages of the bi-level co-optimization approach over the traditional optimization approach. Conclusions of this work illustrate that the stochastic rolling horizon approach could effectively manage the operation of a microgrid with various demand response programs. In addition, the bi-level approach is a promising co-optimization framework for the transmission and distribution levels that could increase system renewable penetration and reduce operation costs. Compared to the traditional framework, the bi-level framework yields more equitable cost sharing patterns among the market participants as well as better support for the power system evolution.

24 POWER TRANSMISSION AND DISTRIBUTION↗
DOE OSTI2018

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↗
DOE OSTI2024

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↗
DOE OSTI2024

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↗
DOE OSTI2024

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↗
DOE OSTI2021

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↗
DOE OSTI2022

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↗
NASA NTRS1999

Ionized Outflows in 3-D Insights from Herbig-Haro Objects and Applications to Nearby AGN

HST shows that the gas distributions of these objects are complex and clump at the limit of resolution. HST spectra have lumpy emission-line profiles, indicating unresolved sub-structure. The advantages of 3D over slits on gas so distributed are: robust flux estimates of various dynamical systems projected along lines of sight, sensitivity to fainter spectral lines that are physical diagnostics (reddening-gas density, T, excitation mechanisms, abundances), and improved prospects for recovery of unobserved dimensions of phase-space. These advantages al- low more confident modeling for more profound inquiry into underlying dynamics. The main complication is the effort required to link multi- frequency datasets that optimally track the energy flow through various phases of the ISM. This tedium has limited the number of objects that have been thoroughly analyzed to the a priori most spectacular systems. For HHO'S, proper-motions constrain the ambient B-field, shock velocity, gas abundances, mass-loss rates, source duty-cycle, and tie-ins with molecular flows. If the shock speed, hence ionization fraction, is indeed small then the ionized gas is a significant part of the flow energetics. For AGN'S, nuclear beaming is a source of ionization ambiguity. Establishing the energetics of the outflow is critical to determining how the accretion disk loses its energy. CXO will provide new constraints (especially spectral) on AGN outflows, and STIS UV-spectroscopy is also constraining cloud properties (although limited by extinction). HHO's show some of the things that we will find around AGN'S. I illustrate these points with results from ground-based and HST programs being pursued with collaborators.

Cecil, Gerald↗
DOE OSTI2020

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↗
DOE OSTI2020

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↗
DOE OSTI2017

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 ↗
NASA NTRSDate not supplied

High Energy Hydroforming Friction Stir Welded 2050 Al-Li Blanks for Aerospace Domes and Cones

Friction stir welded (FSW) aluminum blanks offer larger preform sizes than available from the mill in single width plates. Large blanks made from aerospace-grade aluminum alloys are essential for making large domes and cones for launch vehicles and crew vehicles. Previous research efforts have demonstrated >5m FSW blanks can be formed into large domes or cones using spin forming, but the subsequent solution heat treatment consistently led to abnormal grain growth (AGG). The AGG phenomenon occurs because the FSW blanks must be spin formed in the -O annealed temper to withstand the high strain process without cracking. Subsequently, the solution heat treatment process leads to the onset of AGG, whereby a small number of grains grow much larger than the surrounding matrix. Ultimately, the large grains and bimodal grain-size distribution leads to unacceptable ductility in the short-transverse direction of the part. Alternatively, explosive hydroforming is a nascent process that can be applied to large and thick aerospace-grade aluminum alloy blanks in the -T3 temper and only require a post-forming artificial aging process to a -T8. Avoiding the solution heat treatment (SHT) process mitigates AGG, and also eliminates the need for very rare drop-furnace quench baths that can accommodate a part size larger than 5m in diameter. This presentation summarizes a Lockheed Martin-led effort that demonstrated explosive hydroforming of a 1.9m diameter, 39mm thick 2050 aluminum lithium FSW blank. Details will be provided on the process flow, mechanical properties, and metallographic analyses. This work was performed in partnership with NASA Langley Research Center (LaRC) under a NASA Announcement of Collaboration Opportunities program.

Friction stir welded blank↗