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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 271 records · Page 15
All sourcesNASA NTRSDOE OSTI
DOE OSTI2018

The Holy Grail of Resource Assessment: Low Cost Ground-Based Measurements with Good Accuracy: Preprint

Using performance data from some of the millions of installed photovoltaic (PV) modules with micro-inverters may afford the opportunity to provide ground-based solar resource data critical for developing PV projects. The method used back-solves for the direct normal irradiance (DNI) and the diffuse horizontal irradiance (DHI) from the micro-inverter ac production data. When the derived values of DNI and DHI were then used to model the performance of other PV systems, the annual mean bias deviations were within plus or minus 4 percent, and only 1 percent greater than when the PV performance was modeled using high quality irradiance measurements. An uncertainty analysis shows the method better suited for modeling PV performance than using satellite-based global horizontal irradiance.

14 SOLAR ENERGY↗
DOE OSTI2023

An adjoint-based optimization method for jointly inverting heterogeneous material properties and fault slip from earthquake surface deformation data

SUMMARY Analysis of tectonic and earthquake-cycle associated deformation of the crust can provide valuable insights into the underlying deformation processes including fault slip. How those processes are expressed at the surface depends on the lateral and depth variations of rock properties. The effect of such variations is often tested by forward models based on a priori geological or geophysical information. Here, we first develop a novel technique based on an open-source finite-element computational framework to invert geodetic constraints directly for heterogeneous media properties. We focus on the elastic, coseismic problem and seek to constrain variations in shear modulus and Poisson’s ratio, proxies for the effects of lithology and/or temperature and porous flow, respectively. The corresponding nonlinear inversion is implemented using adjoint-based optimization that efficiently reduces the cost function that includes the misfit between the calculated and observed displacements and a penalty term. We then extend our theoretical and numerical framework to simultaneously infer both heterogeneous Earth’s structure and fault slip from surface deformation. Based on a range of 2-D synthetic cases, we find that both model parameters can be satisfactorily estimated for the megathrust setting-inspired test problems considered. Within limits, this is the case even in the presence of noise and if the fault geometry is not perfectly known. Our method lays the foundation for a future reassessment of the information contained in increasingly data-rich settings, for example, geodetic GNSS constraints for large earthquakes such as the 2011 Tohoku-oki M9 event, or distributed deformation along plate boundaries as constrained from InSAR.

Geochemistry & Geophysics↗
DOE OSTI2019

Methods of resolving artifacts in Hadamard-transformed data

Apparatus and methods are disclosed for processing data transformed according to an invertible transform (e.g., using a Hadamard transform) multiplexing scheme. In one example of the disclosed technology, a computer-implemented method includes generating transformed data by applying a Hadamard transform to intensity data generated by modulating input of analytes into a mass spectrometer according to a pseudorandom sequence (PRS). The exemplary method further includes identifying at least one pair of symmetric intensity peaks in the transformed data based on the PRS and removing data associated with the pair of symmetric peaks from the transformed data to produce modified data, which can be used to identify, characterize, and/or quantify the composition of the sample. In some examples, the exemplary method further includes validating peaks in the transformed data based on comparing the location of peaks in the untransformed intensity data.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2019

Photovoltaic Inverter Reliability Assessment

As the price of PV modules drops, the price of power electronics become more important. Power electronics now constitute 8%-12% of the total lifetime PV cost. As of 2010, the inverter and associated power conditioning components accounted for $\$0.25$/W, well above the DOE benchmark of $\$0.12$/W by 2020. As efforts to reduce PV module costs yield diminishing returns, the importance of understanding and reducing inverter costs becomes an increasingly critical and cost-effective investment toward achieving the DOE SunShot goals. With this in view, this report showcases and describes an approach to help assess and predict the reliability of photovoltaic (PV) inverters. To predict the reliability, thermal cycling is considered as a prominent stressor in the inverter system. To evaluate the impacts of thermal cycling, a detailed linearized model of the PV inverter is developed along with controllers. This research also develops models and methods to compute the losses of the power electronics switches and other components in a PV inverter. The losses are then used to estimate the junction and heat sink temperature. The model is verified by developing an in-house inverter. Additionally, to assess the scalability of the research, the hardware inverter is placed inside a thermal chamber to verify the losses for different ambient temperatures. After the verification of the model, a reduced-order model of the inverter is implemented to translate the profile of ambient temperature and solar irradiance into the profile of junction temperatures of the switches. The estimated junction temperature data are used to identify inverter reliability indices and predict the useful lifetime of the inverter system. After developing the models to predict the useful lifetime of the system, the impact of reactive power on the overall reliability of the system will be studied. The first chapter involves the motivation behind the research on assessing the reliability of PV inverters. The inverter power stage and controller design of the power converter used in this research is also explained in detail in this chapter. The second chapter presents the various losses of the power converter system and the translation of power loss into temperature increase with thermal modeling. The results of the loss modeling and the thermal modeling are also explained in detail in this chapter. The third chapter involves implementing the reduced-order model to translate the mission profile of ambient temperature and solar irradiance into profile of the junction temperatures of the switches. The final chapter involves identifying reliability indices, which are of interest for this system to predict the remaining useful life of the system, and concludes with the impact of reactive power on the overall reliability of the inverter system.

14 SOLAR ENERGY↗
DOE OSTI2024

Interpreting strain tensor data to characterize and monitor reservoirs for CO2 storage and other applications

Recent advances in instrumentation have made it feasible to measure the transient strain tensor caused by small changes in fluid volume or pressure in the subsurface and this has opened the door to new opportunities for characterization and monitoring. We have deployed strainmeters and then conducted injection well tests in an underlying reservoir at 530m depth. The resulting data indicated that the horizontal strain at shallow strainmeters (30 to 40m depth) was tensile and the vertical strain was compressive. The radial strain was less than the horizontal strain, and the strain rates decreased from 100 nanostrain/day to roughly 10 n/d over a few days. The signal at two strainmeters at shallow depth were consistent, although the magnitude of the horizontal strains were different reflecting the different radial directions from the well. The signal at a deep strainmeter deployed at reservoir depth was much different, with tensile vertical strains and compressive horizontal strains. These data can be interpreted by inverting poroelastic forward models developed using numerical and analytical methods. The average horizontal strain in the caprock resembles the transient pressure in the underlying reservoir and classic type-curve methods from transient well testing can be used for preliminary interpretations of strain data. We have developed closed-form analytical solutions to a pressurized poroelastic inclusion and inhomogeneity in a half-space. This model is fast and can be inverted to estimate reservoir stiffness and geometry. Numerical models developed using finite element methods allow more details of the subsurface to be included in the inversion, but they require much longer run times and this makes inversion cumbersome using standard methods. We have developed an inversion approach that uses a proxy model created using machine learning to do most of the forward calculations. The proxy model is periodically updated and refined using the finite element model to ensure accuracy. This approach significantly reduces the computational requirements and makes it feasible to use Bayesian inversion with large numerical models. We have shown that the strain tensor in the caprock is sensitive to pressure in the reservoir, boundaries in the reservoir, and pressure in the caprock caused by leaks. These results indicate that coupling strain tensor data with inversion has the potential to help evaluate reservoirs during initial characterization, and to monitor them during the CO2 injection and storage process.

Murdoch, Larry↗
DOE OSTI2022

Making Invisible Visible: Data-Driven Seismic Inversion With Spatio-Temporally Constrained Data Augmentation

Deep learning and data-driven approaches have shown great potential in scientific domains. The promise of data-driven techniques relies on the availability of a large volume of high-quality training datasets. Due to the high cost of obtaining data through expensive physical experiments, instruments, and simulations, data augmentation techniques for scientific applications have emerged as a new direction for obtaining scientific data recently. However, existing data augmentation techniques originating from computer vision yield physically unacceptable data samples that are not helpful for the domain problems that we are interested in. In this article, we develop new data augmentation techniques based on convolutional neural networks. Specifically, our generative models leverage different physics knowledge (such as governing equations, observable perception, and physics phenomena) to improve the quality of the synthetic data. To validate the effectiveness of our data augmentation techniques, we apply them to solve a subsurface seismic full-waveform inversion using simulated CO 2 leakage data. Our interest is to invert for subsurface velocity models associated with very small CO 2 leakage. We validate the performance of our methods using comprehensive numerical tests. Here via comparison and analysis, we show that data-driven seismic imaging can be significantly enhanced by using our data augmentation techniques. Particularly, the imaging quality has been improved by 15% in test scenarios of general-sized leakage and 17% in small-sized leakage when using an augmented training set obtained with our techniques.

58 GEOSCIENCES↗
DOE OSTI2024

Photovoltaic Inverter Failure Mechanism Estimation Using Unsupervised Machine Learning and Reliability Assessment

This article introduces a data-driven approach to assessing failure mechanisms and reliability degradation in outdoor photovoltaic (PV) string inverters. The manufacturer's stated PV inverter lifetime can vary due to the impact of operating site conditions. To address limitations in degradation estimation through accelerated testing, condition monitoring, or degradation modeling, we propose a machine learning (ML) oriented approach. Utilizing data from a 1.4 MW PV power plant operational since 2016, with 46 string PV inverters tied to the grid, we employ the unsupervised one-class support vector machine ML technique to analyze inverter and sensor data, capable of classifying humidity cycling and temperature fluctuations as dominant failure mechanisms. Utilizing the anomaly alert relationship and alert details specific to the inverter, the level of PV inverter output is considered as its availability or available reliability. Subsequently, a continuous Markov model is applied to six-month alert data, revealing an average stated reliability of 20% after 20 years of continuous operation. These results support recommendations for time-bound preventive measures to enhance PV inverter reliability under diverse outdoor conditions. Furthermore, the approach provides a nondestructive, top–down, and generalized method for analyzing any commercial PV inverter exposed to outdoor conditions, contingent on the availability of relevant data.

14 SOLAR ENERGY↗
DOE OSTI2017

A rock physics and seismic reservoir characterization study of the Rock Springs Uplift, a carbon dioxide sequestration site in Southwestern Wyoming

We present a reservoir geophysics study, including rock physics modeling and seismic inversion, of a carbon dioxide sequestration site in Southwestern Wyoming, namely the Rock Springs Uplift, and build a petrophysical model for the potential injection reservoirs for carbon dioxide sequestration. Our objectives include the facies classification and the estimation of the spatial model of porosity and permeability for two sequestration targets of interest, the Madison Limestone and the Weber Sandstone. The available dataset includes a complete set of well logs at the location of the borehole available in the area, a set of 110 core samples, and a seismic survey acquired in the area around the well. The proposed study includes a formation evaluation analysis and facies classification at the well location, the calibration of a rock physics model to link petrophysical properties and elastic attributes using well log data and core samples, the elastic inversion of the pre-stack seismic data, and the estimation of the reservoir model of facies, porosity and permeability conditioned by seismic inverted elastic attributes and well log data. In particular, the rock physics relations are facies-dependent and include granular media equations for clean and shaley sandstone, and inclusion models for the dolomitized limestone. The permeability model has been computed by applying a facies-dependent porosity-permeability relation calibrated using core sample measurements. Finally, the study shows that both formations show good storage capabilities. The Madison Limestone includes a homogeneous layer of high-porosity high-permeability dolomite; the Weber Sandstone is characterized by a lower average porosity but the layer is thicker than the Madison Limestone.

58 GEOSCIENCES↗
DOE OSTI2023

Hawai‘i Play Fairway (Final Report)

Most of Hawai'i's geothermal resources are blind—their manifestations, such as hot springs and steam vents, do not appear on the ground surface because the heated water flows far below. With the exception of $K\bar{i}lauea East Rift Zone$, in most areas of Hawai'i, high lateral permeability in the first kilometer below ground surface prevents surface thermal features from developing. As a methodology for discovering these blind resources, Play Fairway Analysis (PFA) involves finding potential locations of blind hydrothermal systems and describing potential geothermal sources in rift-zone settings. Using the PFA to find Hawai'i's geothermal resources, the University of Hawai'i (UH) conducted the Hawai‘i Play Fairway Project, Hawai'i's first statewide geothermal resource assessment since 1985. Sponsored by the U.S. Department of Energy, the Hawai'i Play Fairway Project provided an updated resource assessment, a roadmap for additional exploration activities, and the identification of areas for further exploration. Benefitting from UH's core competency in earth sciences and experienced geothermal researchers, the project comprised three phases. During the first phase, the team identified, compiled, and ranked existing geologic, groundwater, and geophysical datasets relevant to subsurface heat, fluid and permeability. Using a Bayesian statistical approach, the team developed a statistical methodology to integrate these data into a resource probability map. The team evaluated the confidence in the probability value and considered development viability of areas with geothermal resources. With these analyses, the team identified 10 locations in the Hawaiian Islands for exploration activities. For the second phase, the team collected new groundwater data in 10 locations across the state and new geophysical data on $L\bar{a}na‘i, Maui$, and central Hawai'i Island and modeled topographically induced stress to better characterize subsurface permeability. Analyzing the subsurface stresses, the team evaluated the potential for fracture-induced permeability. The team inverted the MT and gravity data to produce 3D models of resistivity and density, respectively, on $L\bar{a}na‘i$, across $Haleakal\bar{a}'s$ SW rift (Maui), and surrounding Mauna Kea (Hawai‘i Island). The team developed and applied a new method for incorporating depth information about resistivity, density, and potential for fracture-induced permeability into the statistical method for computing resource probability in these three focus areas. The team incorporated the new groundwater results with the new geophysical results and the calculations of potential for fracture-induced permeability to produce updated maps of resource probability and confidence. Through combining data from the first and second phases, the team determined locations for further exploration during the third phase. For MT and gravity surveys, the team recommended $Kaua'i's$ $L\bar{i}hu'e$ $Basin$, the east rift of $Maui's$ $Haleakal\bar{a}$ volcano, and the southwest rift of Hawai'i Island's Mauna Loa volcano. The MT and gravity surveys aimed to enable improved confidence in the resource potential in these locations. For drilling deep groundwater well(s), the team recommended Southeast Mauna Kea and $L\bar{a}na's$ $P\bar{a}l\bar{a}wai$ $Basin$. During the third phase, further exploration involved drilling a groundwater well in $L\bar{a}na's$ $P\bar{a}l\bar{a}wai$ $Basin$ and performing more geophysical surveys. We deepened an existing water well proximal to our target area on $L\bar{a}na'i$ due to funding constraints that precluded us from spudding a new well that would exceed 1km depth. Drilling was preceded by a number of substantial elements including: writing an Environmental Assessment and the subsequent legal process, performance of deviation logging, lowering a camera down the well, coordinating site preparation with $P\bar{u}lama$ $L\bar{a}na'i$, shipping the UH-owned rig interisland, procuring supplies, and leading 3 community meetings on $L\bar{a}na'i$. Drilling occurred 24/7 the entire month of June 2019 over which time $L\bar{a}na'i$ $Well$ 10 was deepened from 427 m to 1057 m, with continuous core collected. We measured a roughly linear temperature gradient averaging 42°C/km and a maximum bottom hole temperature of 66°C. This gradient is more than twice the background for Hawai'i and within a range of gradients measured in this depth range for some exploration wells within KERZ. We consider these results encouraging for $L\bar{a}na'i's$ resource potential and recommend following with a slim hole within $L\bar{a}na'i's$ caldera (our target zone) to ~ 2 km. Further, the positive implications such results have for the island of O‘ahu are substantial - the shield stage of O'ahu's volcanoes ended 1-2 My earlier. However, O'ahu uses more electricity than the rest of the islands combined, and the utility recently called for 500-700MW of firm, dispatchable renewable electricity on O'ahu by 2033. In Phase 3, we also collected limited new encouraging groundwater data, and updated our thoughts on the probabilities of fluid and permeability at resource depths (Pr F = 1; Pr P = mostly unconstrained). Ultimately, we advocate for using our final probability of heat, and confidence in this probability, to drive the next phase of exploration. We contend further development of geothermal in Hawai‘i will enable the state to achieve its 100% renewable policy objective and Hawai'i to transition off of fossil fuels through geothermal discovery and development. The project not only produced a large amount of data and expanded the existing knowledge of Hawai'i's geothermal resources, but also produced publications, theses, presentations, core photos, datasets, media reports, television interviews, community events, and a blog. Students and new professionals benefitted from the project's hands-on research experiences and educational opportunities and earned awards and recognition.

15 GEOTHERMAL ENERGY↗
DOE OSTI2022

Inverter Reliability Estimation for Advanced Inverter Functionality

In the near future, grid operators are expected to regularly use advanced distributed energy resource (DER) functions, defined in IEEE 1547-2018, to perform a range of grid-support operations. Many of these functions adjust the active and reactive power of the device through commanded or autonomous modes, which will produce new stresses on the grid-interfacing power electronics components, such as DC/AC inverters. In previous work, multiple DER devices were instrumented to evaluate additional component stress under multiple reactive power setpoints. We utilize quasi-static time-series simulations to determine voltage-reactive power mode (volt-var) mission profile of inverters in an active power system. Mission profiles and loss estimates are then combined to estimate the reduction of the useful life of inverters from different reactive power profiles. It was found that the average lifetime reduction was approximately 0.15% for an inverter between standard unity power factor operation and the IEEE 1547 default volt-var curve based on thermal damage due to switching in the power transistors. For an inverter with an expected 20-year lifetime, the 1547 volt-var curve would reduce the expected life of the device by 12 days. This framework for determining an inverter's useful life from experimental and modeling data can be applied to any failure mechanism and advanced inverter operation.

component degradation↗
DOE OSTI2019

Phase retrieval for Bragg coherent diffraction imaging at high x-ray energies

Coherent x-ray beams with energies ≥ 50 keV can potentially enable three-dimensional imaging of atomic lattice distortion fields within individual crystallites in bulk polycrystalline materials through Bragg coherent diffraction imaging (BCDI). However, the undersampling of the diffraction signal due to Fourier-space compression at high x-ray energies renders conventional phase-retrieval algorithms unsuitable for three-dimensional reconstruction. To address this problem, we utilize a phase-retrieval method with a Fourier constraint specifically tailored for undersampled diffraction data measured with coarse-pitched detector pixels that bin the underlying signal. With our approach, we show that it is possible to reconstruct three-dimensional strained crystallites from an undersampled Bragg diffraction data set subject to pixel-area integration without having to physically upsample the diffraction signal. Using simulations and experimental results, we demonstrate that explicit modeling of Fourier-space compression during phase retrieval provides a viable means by which to invert high-energy BCDI data, which is otherwise intractable.

74 ATOMIC AND MOLECULAR PHYSICS↗
DOE OSTI2021

Dynamic Inverter Characterization for Modeling

The goal of the project was to develop data to be used for modeling the dynamic characteristics of smart inverters. The inverters were tested in both a lab setting, and a subset was deployed in residential homes for longer term data collection during real-world use.

24 POWER TRANSMISSION AND DISTRIBUTION↗
NASA NTRS1990

Dayside auroral particle acceleration mechanisms derived from Dynamics Explorer data

The characteristics of dayside electron acceleration regions, or inverted V's, and the nature of the field-aligned currents flowing in their vicinity are studied by using data from Dynamics Explorer hot-plasma and magnetic-field instruments. It is shown that dayside inverted-V events are common features of the mid-altitude extension of the boundary layer, which lies equatorward of the cusp. Upward-accelerated ionospheric electron beams are found to be carriers of downward region-1 currents even in regions of downward electron acceleration. It is not clear, however, how the upward-accelerated cold electron beams can exist above an apparent upward parallel electric field, since such a potential different would tend to confine the cold ionospheric electrons to low altitudes.

Burch, J. L.↗
DOE OSTI2020

Self-Secure Inverters Against Malicious Setpoints

The next generation of grid-interactive inverters brings a communication feature that allows data sharing from utility supervisory controllers and smart devices that are connected to the same network. This feature enhances the control capabilities of grid-interactive inverters to provide services beyond active power injection. However, communication networks entail more vulnerable surfaces to malicious attacks that may result in modifying active and reactive power setpoints and causing weak-grid conditions or abnormal inverter operation. In this paper, steady-state and the dynamic behavior of the inverter for the incoming setpoints are analyzed to detect false data injection attacks and provide device-level security. The steady-state behavior of the inverter in the operating region is determined from the grid parameters such as the grid voltage and the grid impedance. These estimations are accomplished by the proposed self-security technique through a low-frequency signal injection-based approach combined with the recursive least square method. Moreover, a reduced fourth-order inverter model is used as the dynamic reference model, and grid parameters as well as the incoming setpoints are implemented to the reference model to verify whether the dynamic behavior of the inverter is inside the permissible region of operation. The validity and performance of the proposed method are verified experimentally through Allen-Bradley Powerflex 755 three-phase inverter and a 12 kW NHR 9410 regenerative power grid emulator. The results show that the self-secure smart-inverter is able to accept or reject the incoming commands and thus is protected from malicious cyber-physical attacks.

Hossen, Tareq↗
DOE OSTI2022

Common Information Model for Electromagnetic Transients (CIM for EMT): CRADA 533 [Abstract only}

The control and protection functions of inverter-based resources (IBR) have raised concerns with bulk system reliability. Most of the current interest lies with solar photovoltaic generation but increasing amounts of storage would pose the same risks. Newer North American Electric Reliability Corporation (NERC) guidelines call for electromagnetic transient (EMT) studies of IBR and recommend that transmission operators collect distributed energy resource (DER) data to support such modeling. IEEE Standard P2800.1 is defining tests for model parameterization, so good model data should become available from inverter vendors. (EMT studies also apply to large power transformer reliability, and transformer vendors can provide EMT models.) Utilities don’t currently have the rest of the bulk system represented for EMT studies at large scale. An International Electrotechnical Commission (IEC) standard Common Information Model (CIM) provides a way of supporting these detailed models from physical asset data, e.g., conductors, towers, transformer data sheets, control block diagrams, while avoiding software vendor lock-in. CIM-for-EMT, with proposed schema extensions and open-source converters, provides a way to exchange EMT data between organizations and tools. This project leverages Office of Electricity (OE) funding of CIM-for-EMT code base through the GridAPPS-DTM project, and of GridPACKTM (parallelized transmission solver), for interoperability testing in CIM-for-EMT. The project also leverages partner PGSTech investments in EMTP® interoperability with CIM.

24 POWER TRANSMISSION AND DISTRIBUTION↗
DOE OSTI2018

Frequency-domain full-waveform inversion with non-linear descent directions

Full-waveform inversion (FWI) is a highly non-linear inverse problem, normally solved iteratively, with each iteration involving an update constructed through linear operations on the residuals. Incorporating a flexible degree of non-linearity within each update may have important consequences for convergence rates, determination of low model wavenumbers and discrimination of parameters. In this study, we examine one approach for doing so, wherein higher order scattering terms are included within the sensitivity kernel during the construction of the descent direction, adjusting it away from that of the standard Gauss–Newton approach. These scattering terms are naturally admitted when we construct the sensitivity kernel by varying not the current but the to-be-updated model at each iteration. Linear and/or non-linear inverse scattering methodologies allow these additional sensitivity contributions to be computed from the current data residuals within any given update. We show that in the presence of pre-critical reflection data, the error in a second-order non-linear update to a background of s 0 is, in our scheme, proportional to at most (Δs/s 0 ) 3 in the actual parameter jump Δs causing the reflection. In contrast, the error in a standard Gauss–Newton FWI update is proportional to (Δs/s 0 ) 2 . For numerical implementation of more complex cases, we introduce a non-linear frequency-domain scheme, with an inner and an outer loop. A perturbation is determined from the data residuals within the inner loop, and a descent direction based on the resulting non-linear sensitivity kernel is computed in the outer loop. We examine the response of this non-linear FWI using acoustic single-parameter synthetics derived from the Marmousi model. Lastly, the inverted results vary depending on data frequency ranges and initial models, but we conclude that the non-linear FWI has the capability to generate high-resolution model estimates in both shallow and deep regions, and to converge rapidly, relative to a benchmark FWI approach involving the standard gradient.

58 GEOSCIENCES↗