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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 OSTI2022

Long Term Damage Testing (NREL)

DOE's Regional Test Center program has fielded several strings of PV modules as part of their Long Term Testing program. Some of these modules have been installed since 2016 and have been exposed to severe weather events. A key to developing long lifespans for PV modules (in excess of 30 years) is understanding how damage and defects develop, propagate and progress. Researchers at the NREL Regional Test Center have started developing testing procedures and analysis tools in order to characterize modules in a controlled manner with the goal of understanding how damage spreads under normal operations. Characterization methods include EL and IR imaging, outdoor and indoor IV curves, and long term exposure monitoring. Modules to be evaluated will be chosen based on severity of defect, ability to track changes in defect and space requirements. The samples will be loaded at maximum power using grid-tied inverters or other means. Gathering and reporting on this data may help engineers and scientists design for damage and improve long-term performance.

crack damage↗
DOE OSTI2024

Geophysical and Environmental Monitoring Data, and Subsurface Flow Modelling Results for Chicken Bone Meadow, Mt. Snodgrass, Crested Butte, CO

This dataset includes geoelectrical monitoring data acquired between October 2021 and November 2022, soil moisture and temperature data, groundwater data obtained from borehole SNIB covering the period from June 2021 to September 2022, and hydrological modelling results. The data were acquired to investigate how variations in bedrock type and topography, and vegetation cover control subsurface flow dynamics. To provide insights into the subsurface flow dynamics and their controls, a monitoring transect was installed at the Chicken Bone Meadow, Mt. Snodgrass, Crested Butte, CO, measuring the spatio-temporal variations of soil moisture, soil and snow temperature, subsurface electrical resistivity variations, and groundwater dynamics. Field data are organized in a folder structure, with Electrical Resistivity Tomography (ERT) data being provided as one file per measurement, and data of the soil moisture and temperature sensors being provided as text files covering the entire monitoring period. The ‘Locations.csv’ file contains the location of all sensors, given in NAD83 – UTM Zone 13N. ERT monitoring data has been processed to filter data based on reciprocal errors (data with errors > 30% were removed), a linear error model was fitted to each survey, and to ensure a constant set of measurements for time-lapse inversion, filtered data were interpolated and assigned a 100% measurement error. Soil moisture and temperature data were acquired at 15 min intervals, and averaged to provide 1h data. Weather data and borehole data (groundwater depth, conductivity and temperature) were acquired at 30 min intervals, and are provided as daily measurements; all measurements are averaged, except of precipitation values, which are given as daily accumulation. The hydrological model was set up along the ERT monitoring transect, and net infiltration was used as surface boundary condition and derived from the weather data. Four different results are provided, (1) results for a parameterization using hydraulic permeability and porosity as derived from the ERT data through petrophysical relationships, and (2) three simplified model results, using 1 to 3 geological layers above the bedrock. Modelling was performed using PFLOTRAN, and for each model the PFLOTRAN input files are provided. The result files include weekly hydrological modelling results (e.g., saturation, velocities, pressures), as well as the model parameterization. The dataset additionally includes a file-level metadata (flmd.csv) file that lists each file contained in the dataset with associated metadata; and a data dictionary (dd.csv) file that contains column/row headers used throughout the files along with a definition, units, and data type.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2021

Retiring environmental risks of marine renewable energy devices: The “habitat change” case

The installation, presence, operation, and decommissioning of marine renewable energy (MRE) devices inevitably alters the surrounding ocean habitats. These changes may include direct effects on the benthos from the installation or removal of foundations and anchors, changes in community composition on and near devices, artificial reef effects, and indirect effects such as alteration of the food web or facilitation of non-native, invasive species dispersal. Although there is no expectation that MRE devices affect marine environments differently than other anthropogenic ocean uses, regulators and stakeholders continue to have questions about potential negative impacts to species and habitats from development. Research studies and survey reports that inform our understanding of habitat changes related to MRE devices and associated equipment were compiled into an evidence base, sorted into categories of effects, and evaluated by a group of international experts to assess potential risk to habitats and biota from small numbers of MRE devices, as well as to identify knowledge gaps. These gaps were organized by category and divided up by relevance to consenting, research, or project development and monitoring responsibilities. Identifying these “known unknowns” allows for study design and collaboration from various perspectives to fill the knowledge gaps. Distribution of the evidence base and remaining uncertainties and knowledge gaps to the MRE community, coupled with new research, will help advance the MRE industry while resolving concerns about the potential risks of habitat change for small numbers of devices.

Hemery, Lenaig G.↗
DOE OSTI2022

Status of the data acquisition, trigger, and slow control systems of the Mu2e experiment at Fermilab

The Mu2e experiment at the Fermilab will search for a coherent neutrinoless conversion of a muon into an electron in the field of an aluminum nucleus with a sensitivity improvement by a factor of 10,000 over existing limits. In this work, the Mu2e Trigger and Data Acquisition System (TDAQ) uses otsdaq framework as the online Data Acquisition System (DAQ) solution. Developed at Fermilab, otsdaq integrates several framework components — an artdaq-based DAQ, an art-based event processing, and an EPICS-based detector control system (DCS), and provides a uniform multi-user interface to its components through a web browser. Data streams from the Mu2e tracker and calorimeter are handled by the artdaq-based DAQ and processed by a one-level software trigger implemented within the art framework. Events accepted by the trigger have their data combined, post-trigger, with the separately read out data from the Mu2e Cosmic Ray Veto system. Foundation of the Mu2e DCS, EPICS – an Experimental Physics and Industrial Control System – is an open-source platform for monitoring, controlling, alarming, and archiving. A prototype of the TDAQ and the DCS systems has been built and tested over the last three years at Fermilab’s Feynman Computing Center, and now the production system installation is underway. This work presents their status and focus on the installation plans and procedures for racks, workstations, network switches, gateway computers, DAQ hardware, slow controls implementation, and testing.

46 INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AND ↗
DOE OSTI2022

Flexible organic integrated electronics for self-powered multiplexed ocular monitoring

Smart contact lens has drawn extensive research interests due to the noninvasive real-time detection of the human body to provide biomedical information for health management. However, it has been difficult to accurately measure the physiological signals in tears, and the use of external power source has also hindered the future applications. Here, we demonstrated an organic electrochemical transistor based multiplexed sensors self-powered by the organic solar cells (OSCs). The integrated device was fabricated via simple process including solution blade-coating and thermal evaporation. OSCs were optimized to provide optimal operation voltage for the sensors that exhibit semilog-linear response to the glucose and calcium ions in tear fluids without any peripheral circuits. The sensing signals can be transmitted to the laptop wirelessly through a near filed communication unit. This integrated self-powered multiplexed sensing device will provide real-time monitoring of the biomarkers in tears, prospected to be installed on the smart contact lens for the early detection and diagnosis of diabetes.

36 MATERIALS SCIENCE↗
DOE OSTI2024

A near X-point charge exchange neutral spectroscopy (CENS) system for DIII-D

A 16 channel spectroscopy system has been installed on DIII-D to provide information about the energy distribution of the atomic neutrals using the Doppler shift and broadening of passive Balmer-α emission. Here, the lines of sight are dominantly in the toroidal direction, with tangencies near the lowest point on closed magnetic flux surfaces moving from the lower divertor upward into the confined plasma. This allows the system to provide details of the neutrals as they undergo various atomic physics processes while traveling upward from the lower divertor. The spectrally resolved measurements provide several advantages that complement typical optical filter based measurements of hydrogenic spectral lines. These include more direct measurements of the neutrals that fuel deeper in the plasma and capturing neutral velocity distribution information via the Doppler broadened and shifted line. In addition, the spectral separation of higher energy “thermal” neutrals and bright cold emission from the scrape-off layer allows for a more straightforward calculation of the underlying neutral densities based on the emission because of the dependence of the thermal emission on confined plasma properties that are approximately flux functions and well measured.

Atomic and molecular physics↗
DOE OSTI2021

Hydrogenerate: Open Source Python Tool To Estimate Hydropower Generation Time-series

Hydropower is one of the most mature forms of renewable energy generation. The United States (US) has almost 103 GW of installed, with 80 GW of conventional generation and 23 GW of pumped hydropower [1]. Moreover, the potential for future development on Non-Powered Dams is up to 10 GW. With the US setting its goals to become carbon neutral [2], more renewable energy in the form of hydropower needs to be integrated with the grid. Currently, there are no publicly available tool that can estimate the hydropower potential for existing hydropower dams or other non-powered dams. The HydroGenerate is an open-source python library that has the capability of estimating hydropower generation based on flow rate either provided by the user or received from United States Geological Survey (USGS) water data services. The tool calculates the efficiency as a function of flow based on the turbine type either selected by the user or estimated based on the “head” provided by the user.

Mitra, Bhaskar↗
DOE OSTI2021

Experimental Plan for the Vermiculite Study

Homes in which vermiculite, which can contain asbestos, is present are often deferred under the DOE Weatherization Assistance Program (WAP) because of uncertainty in how to safely weatherize such homes from a client and worker perspective and the potential costs associated with alternative approaches. Recognizing this situation, the Department of Energy (DOE) tasked the Oak Ridge National Laboratory (ORNL) to perform a research project that scientifically identifies the asbestos exposure risks in weatherizing homes with existing vermiculite insulation. Current approaches being used by Grantees and Subgrantees to weatherize homes with existing vermiculite insulation were identified as part of the development of this experimental plan based on a review of Grantee Health and Safety Plans and communications with weatherization program staff from seven states. Other than deferral, these approaches include the following:1.) Abating (i.e., removing) the existing vermiculite using funding sources other than WAP (e.g., state funds, utility funds, the Zonolite Attic Insulation Trust Fund, and possibly homeowner contributions) because abatement is not allowed using WAP funds per Weatherization Program Notice (WPN) 17-7. 2.) Weatherizing the house as normal after testing reveals that the vermiculite contains less than 1% asbestos. 3.) Avoiding areas of the house where vermiculite is installed and weatherizing the remaining areas of the house as normal. 4.) Encapsulating the existing vermiculite insulation in an attic by blowing cellulose or other insulation over it. 5.) Weatherizing the areas of the house where vermiculite is installed using unique/alternative approaches developed specifically for that house. Blower door testing is also impacted by the presence of vermiculite due to the concern of bringing asbestos fibers into the space. Some states address this by performing pressurized blower door tests, whereas other states prohibit blower door testing entirely when vermiculite is present. This research project will focus on gathering data on home occupant and weatherization worker exposures to asbestos before, during, and/or after the weatherization of the homes containing vermiculite insulation using five of the six approaches identified above. Abatement of the existing vermiculite insulation will not be studied because it is not allowed using WAP funding per WPN 17-7 and, thus, is not a sustainable approach for WAP.

36 MATERIALS SCIENCE↗
DOE OSTI2021

Phenomenon Identification and Ranking Table Analysis for Thermal Energy Storage Technologies Integration with Advanced Nuclear Reactors

This report provides an overview of the Phenomena Identification and Ranking Table (PIRT) analysis of thermal energy storage (TES) systems for possible integration with various types of advanced nuclear power plants (NPPs). Advanced NPPs will potentially need to operate in environments where power generation flexibility is more highly valued than the stability or baseload generation capability for conventional demand curves. TES systems would enable NPPs to respond nimbly to market variability and could also position advanced NPPs to participate differently in restructured markets, thus further enhancing their economic competitiveness. TES systems could also benefit the electric grid by eliminating the need for peaking plants, as well as by improving the economic performance of baseload NPPs. While TES technologies afford a unique opportunity to address many of these challenges, the applicability of these systems is also complicated by the fact that various advanced NPPs are designed differently, each with its own temperature range, size, operating fluids, and operating conditions. Hence, TES systems face significant barriers to investment, as more information on their compatibility and performance metrics is needed to quantify the advantages provided by each, as well as the challenges these technologies might face if coupled with a particular type of advanced NPP. This report explores the possibility of integrating a wide variety of TES technologies with various categories of advanced NPPs, based on their operating characteristics. To help users and developers decide which TES technology is best suited to a particular category of advanced NPPs, this research developed a PIRT of 10 TES systems that could potentially be coupled with advanced NPPs, which themselves are divided into nine categories based on their operating conditions. Each advanced NPP category is evaluated for compatibility with the 10 TES systems by assembling and discussing a database of information concerning 10 engineering questions (defined herein in as figures of merit [FOMs]), such as: technology readiness level (TRL), temperature compatibility, energy density, size, cycle frequency, ramp time, realignment frequency, geographic needs, environmental impact, and interventions. By assembling a database of information concerning the TES technologies’ compatibility with various advanced NPP systems, this study can help developers acquaint themselves with a particular TES technology before choosing to build a new integrated installation.

22 GENERAL STUDIES OF NUCLEAR REACTORS↗
DOE OSTI2022

Mapping thermal energy storage technologies with advanced nuclear reactors

Advanced nuclear power plants (NPPs) will potentially need to operate in environments where power generation flexibility is more highly valued than the stability or baseload generation capability for conventional demand curves. Thermal energy storage (TES) systems would enable NPPs to respond nimbly to market variability and could also position advanced NPPs to participate differently in restructured markets, thus further enhancing their economic competitiveness. TES systems could also benefit the electric grid by eliminating the need for peaking plants, as well as by improving the economic performance of baseload NPPs. While TES technologies afford a unique opportunity to address many of these challenges, the applicability of these systems is also complicated by the fact that various advanced NPPs are designed differently, each with its own temperature range, size, operating fluids, and operating conditions. Hence, TES systems face significant barriers to investment, as more information on their compatibility and performance metrics is needed to quantify the advantages provided by each, as well as the challenges these technologies might face if coupled with a particular type of advanced NPP. This study explores the possibility of integrating a wide variety of TES technologies with various categories of advanced NPPs, based on their operating characteristics. To help decision makers, users and developers decide which TES technology is best suited to a particular category of advanced NPPs, this research present a Phenomena Identification and Ranking Table (PIRT) analysis of 10 TES systems that could potentially be coupled with advanced NPPs, which themselves are divided into nine categories based on their operating conditions. Then, each advanced NPP category is evaluated for compatibility with the 10 TES systems by assembling and discussing a database of information concerning 10 engineering questions, defined herein in as figures of merit (FOMs), such as: technology readiness level (TRL), temperature compatibility, energy density, size, cycle frequency, ramp time, realignment frequency, geographic needs, environmental impact, and interventions. By assembling a database of information concerning the TES technologies' compatibility with various advanced NPP systems, this study can help developers acquaint themselves with a particular TES technology before choosing to build a new integrated installation.

22 GENERAL STUDIES OF NUCLEAR REACTORS↗
DOE OSTI2020

Water Network Tool for Resilience (WNTR). User Manual, Version 0.2.3

The Water Network Tool for Resilience (WNTR, pronounced winter) is a Python package designed to simulate and analyze resilience of water distribution networks. Here, a network refers to the collection of pipes, pumps, valves, junctions, tanks, and reservoirs that make up a water distribution system. WNTR has an application programming interface (API) that is flexible and allows for changes to the network structure and operations, along with simulation of disruptive incidents and recovery actions. WNTR is based upon EPANET, which is a tool to simulate the movement and fate of drinking water constituents within distribution systems. Users are encouraged to be familiar with the use of EPANET and/or should have background knowledge in hydraulics and pressurized pipe network modeling before using WNTR. EPANET has a graphical user interface that might be a useful tool to facilitate the visualization of the network and the associated analysis results. Information on EPANET can be found at https://www.epa.gov/water-research/epanet. WNTR is compatible with EPANET 2.00.12 [Ross00]. In addition, users should have experience using Python, including the installation of additional Python packages. General information on Python can be found at https://www.python.org/.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2021

Hydraulic Testing of the Lost Lake Aquifer Near Recovery Well RWM019

An aquifer pumping test was conducted on the Lost Lake Aquifer Zone (LLAZ) at the recently installed recovery well RWM019 in accordance with the approved test plan (Dixon, 2020). The objective of the testing was to determine baseline well performance parameters and aquifer hydraulic conductivity. This testing consisted of a step-drawdown test to determine well performance properties, a constant pumping rate aquifer test to determine aquifer hydraulic properties, and a post-test aquifer recovery monitoring period also used to estimate aquifer hydraulic properties. Well performance parameters determined included specific capacity, well efficiency, and head loss coefficients. The specific capacity of RWM019 was determined to be approximately 2.6 gpm/ft of drawdown based on the final step of the step-drawdown test. Well efficiency was inversely related to pumping rate and decreased from 87% to 81% over a pumping range of approximately 49 to 79 gpm. The aquifer head loss coefficient was determined to be 2.3 ft/ft 3 /min and the well loss coefficient was determined to be 0.05 min 2 /ft 5 .

42 ENGINEERING↗
DOE OSTI2026

Heliostat Sizing Methodology for Solar Heat for Industrial Processes

This study presents a method to obtain a heliostat size that minimizes the levelized cost of a heliostat-based concentrating solar thermal system for industrial process heat (IPH) applications at operating temperatures from 565 to 1550 degrees Celsius. The method extends prior work by embedding a routine for system design that obtains near-optimal subsystem sizes, increasing the fidelity of drive cost functions, and adding an optical performance model. An illustrative business case is developed for Daggett, California, targeting specified annual thermal energy outputs of 50 to 400 GWhth. Optical performance is modeled using verified estimates from the literature. A surrogate heliostat cost model, derived from commercial heliostat designs and scaled for production volume, installation, and operations and maintenance costs, is used to develop cost functions. Results show that heliostat size strongly affects the levelized cost of heat (LCOH), producing a characteristic U-shaped trend with a robust near-optimal window of 8 - 12 m2; the heliostat size producing the lowest project cost in our study grows slightly as the project size increases, and is reduced as the operating temperature increases. The findings in this study are consistent with the general trend of smaller heliostats under deployment at existing projects for high-temperature industrial process heat and reflect the significant reduction in power electronics and other per-heliostat costs. The methodology we propose is general and can be tailored to revised cost curves as the technology continues to evolve.

14 SOLAR ENERGY↗
DOE OSTI2026

An Online Tool for Preliminary Design and Techno-Economic Analysis of District Geothermal Heating and Cooling Systems

District geothermal heating and cooling systems (DGHCS) have significant benefits for reducing energy consumption as well as building- and grid-level peak electric demand. Currently, no publicly available tools are available to effectively design and conduct techno-economic analysis of DGHCS. GeoWISE was originally developed for preliminary design and techno-economic analysis of geothermal heating and cooling systems in an individual commercial or residential building. This paper introduces recent upgrades of GeoWISE that allow users to design and conduct techno-economic analysis of DGHCS. Several new features are implemented in GeoWISE to allow selection and specification of multiple new or existing buildings. A database of information for over 125 million existing U.S. buildings was used in GeoWISE that allows users easily locate existing buildings of interest based on street addresses, and optionally edit information of the buildings (e.g., footprint, vintage, principal functions, number of floors, window-to-wall ratio). Unique energy simulation models of the selected buildings are then automatically created using the Automatic Building Energy Modeling (AutoBEM) and EnergyPlus simulations are performed to predict thermal loads of the buildings. A simplified DGHCS is then designed and simulated to predict its energy use. A central borehole heat exchanger (BHE) of the DGHCS is sized using the RowWise algorithm of GHEDesigner to meet the thermal loads within user-specified land areas for installing BHE. The upgraded GeoWISE reports the needed capacity of heating and cooling equipment in each building, design of the central BHE, energy consumption reduction, and energy cost saving resulting from using DGHCS compared with conventional HVAC systems. A case study is showcased using the upgraded GeoWISE to design and conduct techno-economic analysis of a simplified DGHCS.

Prem Anand Jayaprabha, Jyothis Anand [ORNL] (ORCID↗
DOE OSTI2026

Augmenting LLM-Based Agents for Improved Performance in Pentesting and Commissioning Operational Technology in Critical Infrastructure

Artificial intelligence (AI), and more specifically large language models (LLMs) have the potential for use in penetration testing (“pentesting”) against devices, networks, and computer systems in information technology (IT). We explore the possibility of extending pentesting from IT systems to operational technology (OT) systems, which are more obscure than IT systems in their protocols and design. A challenge therefore exists when applying pretrained LLMs to OT systems as corpora are likely to underrepresent OT systems in comparison to other more prevalent systems. We evaluate augmentations of LLMs with various methods, especially retrieval augmented generation (RAG), to improve performance of the LLMs in the OT domain. In addition to pentesting, some of the testing of these OT devices may include commissioning to ensure that the newly installed devices work correctly. Our framework may also be applied in such cases.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2025

Graph-based Simulation Framework for Power Resilience Estimation and Enhancement

The increasing frequency of extreme weather events poses significant risks to power distribution systems, leading to widespread outages and severe economic and social consequences. This paper presents a novel simulation framework for assessing and enhancing the resilience of power distribution networks under such conditions. Resilience is estimated through Monte Carlo simulations, which simulate extreme weather scenarios and evaluate the impact on infrastructure fragility. Due to the proprietary nature of power network topology, a distribution network is synthesized using publicly available data. To generate the weather scenarios, an extreme weather generation method is developed. To enhance resilience, renewable resources such as solar panels and energy storage systems (batteries in this study) are incorporated. A customized Genetic Algorithm is proposed to determine the optimal locations and capacities for solar panels and battery installations, maximizing resilience while balancing cost constraints. Experiment results demonstrate that on a large-scale synthetic distribution network with more than 300,000 nodes and 300,000 edges, the proposed framework can efficiently evaluate the resilience, and enhance the resilience through the installations of distributed energy resources (DERs), providing utilities with valuable insights for community-level power system resilience estimation and enhancement.

Wang, Xuesong [Wayne State Univ., Detroit, MI (Uni↗
DOE OSTI2021

Could on-site fuel storage economically reduce power plant-gas grid dependence in pipeline constrained areas like New England?

In the Northeastern United States, natural gas supply constraints have led to periods when gas shortages have caused up to a quarter of all unscheduled power plant outages. Dual fuel oil/gas generators or local gas storage might mitigate gas supply shortages. We use historical power plant operational and availability data to develop a supply curve of the costs required for generators to mitigate fuel shortage failures in New England. Based on 2012–2018 data, we find that the historical fuel shortages at approximately 2 GW worth of gas-fired capacity could be mitigated using on-site fuel storage. For comparison, New England’s average reserve margin was 1.7–2.8 GW over our sample period. Oil dual fuel plants would recoup their investment if compensated with a reliability adder of $\$ 3-7$/MWh during their normal operations, while $\$ 7-16$/MWh would incentivize using onsite, compressed natural gas storage. We estimate that the capital expenses associated with the fuel storage options would be less expensive than installing battery backup for resource adequacy at current battery prices.

03 NATURAL GAS↗
DOE OSTI2021

Distributed Thermal Response Multi-Source Modeling to Evaluate Heterogeneous Subsurface Properties

A thorough assessment of thermal properties in heterogeneous subsurface is necessary in design of low-temperature borehole heat exchangers (BHEs). For this study, a distributed thermal response test (DTRT), which combines distributed temperature sensing (DTS) with a conventional thermal response test (TRT), was conducted in a U-bend geothermal loop installed in an open borehole at the University of Illinois at Urbana-Champaign to estimate thermal properties by analyzing the thermal response of different geologic materials while applying a constant heat input rate. Fiber-optic cables in the DTRT were deployed both inside the U-bend geothermal loop and in the center of the borehole to improve the accuracy of calculated heat-loss rates and borehole temperature profile measurements. To assess the subsurface thermal conductivity during the heating phase of the DTRT, a single-source model and a multi-source model, both based on the infinite line source method, were developed using the borehole temperature data and temperatures inside and along the outside of the loop, separately. The two models returned similar thermal conductivity values. The multi-source modeling has the advantage of predicting the thermal conductivity of heterogeneous geologic materials from borehole temperature profiles during the DTRT heating phase. Additionally, based on the distributed thermal conductivity measured in the borehole, estimates were made for both radial thermal impacts and the rate of heat loss in the BHE.

58 GEOSCIENCES↗