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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 19 records
All sourcesNASA NTRSDOE OSTI
DOE OSTI2024

Understanding Line Losses and Transformer Losses in Rural Isolated Distribution Systems

Rural, isolated power systems in the mainland U.S. and in states like Alaska and Hawaii are powered by assets like diesel generators. These rural, isolated power systems also cannot operate at the higher band of medium voltage (like 69kV). They are primarily in the 12 to 14 kV range to keep the cost of the distribution investments lower. Because of this mid-band medium voltage range, the line losses and distribution transformers losses consume significant diesel consumption (almost 10 percent of the peak load). This work considers one such power system powering an isolated system and presents key findings online losses, and transformer losses. Understanding and documenting the impacts is critical for these communities operating their power systems and take actions to reduce expensive diesel consumption. In this paper, we will present one such typical grid and model it in electromagnetic transients (EMT) domain. We used the tower structure, under ground cabling installation to develop high fidelity models of lines. We also used high fidelity models of distribution transformers to present the no-load losses and full load loses. We will also present technical solutions available commercially off-the-shelf to reduce these losses and reduce diesel consumption. This work will be a primer for communities to understand the technical challenges and to understand the possible solution available to solve such challenges for rural, isolated power system operators.

blackstart↗
DOE OSTI2020

Machine Learning Methods for Connection RTT and Loss Rate Estimation Using MPI Measurements Under Random Losses

Scientific computations are expected to be increasingly distributed across wide-area networks, and Message Passing Interface (MPI) has been shown to scale to support their communications over long distances. Application-level measurements of MPI operations reflect the connection Round-Trip Time (RTT) and loss rate, and machine learning methods have been previously developed to estimate them under deterministic periodic losses. In this paper, we consider more complex, random losses with unform, Poisson and Gaussian distributions. We study five disparate machine leaning methods, with linear and non-linear, and smooth and non-smooth properties, to estimate RTT and loss rate over 10Gbps connections with 0-366ms RTT. The diversity and complexity of these estimators combined with the randomness of losses and TCP’s non-linear response together rule out the selection of a single best among them; instead, we fuse them to retain their design diversity. Overall, the results show that accurate estimates can be generated at low loss rates but become inaccurate at loss rates 10% and higher, thereby illustrating both their strengths and limitations.

Generalization Bounds↗
DOE OSTI2020

Losses of CO and CO 2 upon collision-activated dissociation of substituted 2-methoxyphenoxides after methyl radical loss

Some deprotonated, substituted 2-methoxyphenols fragment by methyl radical loss followed by competing losses of CO and CO 2 upon collisional activation in linear quadrupole ion trap mass spectrometers. These reactions were examined experimentally and computationally in order to determine their mechanisms. For deprotonated vanillin, the CO loss was found to involve ring contraction, with the highest free energy barrier of 58.0 kcal mol -1 (for the syn rotamer; here, syn refers to the relationship between the aldehyde oxygen atom and the oxygen atom of the methoxy group) for the entire process. The atoms lost in this fragmentation are the oxygen atom that was bound to the first eliminated methyl group and the aromatic carbon atom bound to this oxygen. Examination of carbon-13 labeled vanillin supports these assignments. Examination of several model compounds revealed that this reaction requires the presence of an electron-withdrawing substituent in the para-position relative to the phenol moiety. In contrast, the CO 2 loss from deprotonated vanillin occurs via ring opening followed by re-cyclization and then ring contraction, leading to the loss of CO 2 in a process wherein the highest free energy barrier is 84.5 kcal mol -1 (for the syn isomer). The atoms lost in this fragmentation are the carbon and oxygen atoms from the phenoxide group and the oxygen atom that was bound to the first eliminated methyl group, which is supported by examination of carbon-13 labeled vanillin. Despite the higher total free energy requirement, the CO 2 loss is competitive with CO loss, possibly due to favorable entropy and low activation energy (free energy barrier of 48.9 kcal mol -1 ) for the first reaction step (the analogous value for CO loss is 58.0 kcal mol -1 ). The extent of CO 2 loss is strongly affected by substituents – it either is not observed or is very slow for the other compounds studied here. For example, it is substantially less favorable than CO loss (highest free energy barrier 60.9 kcal mol -1 ) for deprotonated acetovanillone for which the first reaction step for CO 2 loss has a substantially greater free energy barrier (60.6 kcal mol-1) than for vanillin.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗
DOE OSTI2025

Analysis of fast-ion losses measured in MAST-U via infrared thermography and a Fast Ion Loss Detector

Fast-ion losses need to be monitored to avoid damage to plasma facing components. In existing experimental devices, the scintillator-based fast-ion loss detector (FILD) is the most advanced diagnostic for measuring fast-ion losses. However, FILDs provide only local information about the losses. Infrared (IR) thermography can be used as a complementary tool for more global monitoring of the deposition of fast-ion losses on the wall, at the expense of no velocity-space resolution. IR cameras measure the temperature of the plasma facing components. This measurement, determined by a combined effect of the thermal plasma, radiation, neutrons and fast-ion losses, can be decomposed to infer the fast-ion load on the tokamak wall. In this manuscript, a workflow to estimate fast-ion losses via IR thermography is applied to the MAST-U spherical tokamak, using a 1D approximation to extract the experimental heat flux on the FILD front face from IR data. To numerically estimate the different contributions to this total heat flux, the field-line tracing environment SMITER is used to calculate the thermal plasma contribution, the orbit-following Monte-Carlo code ASCOT to estimate the fast-ion losses, and bolometry measurements for the radiation. To validate the workflow, two discharges, L-mode plasmas with low MHD activity, were executed using on and off-axis beams, respectively. The experimentally and numerically estimated heat flux are of the same order of magnitude for the on-axis heated scenario, with a strong dependence of the estimated fast-ion losses contribution on the fit to the kinetic profiles used as input. This is also true for the off-axis heated scenario, where the total numerically estimated heat flux is 2.1 or 1.3 times higher than the maximum experimentally estimated heat flux, depending on the ASCOT input used.

FILD↗
DOE OSTI2025

Nanoscale and Element-Specific Lattice Temperature Measurements Using Core-Loss Electron Energy-Loss Spectroscopy

Measuring nanoscale local temperatures, particularly in vertically integrated and multicomponent systems, remains challenging. Spectroscopic techniques like X-ray absorption and core-loss electron energy-loss spectroscopy (EELS) are sensitive to lattice temperature, but understanding thermal effects is nontrivial. This work explores the potential for nanoscale and element-specific core-loss thermometry by comparing the Si L2,3 edge’s temperature- dependent redshift against plasmon energy expansion thermometry (PEET) in a scanning TEM. Using density functional theory (DFT), time-dependent DFT, and the Bethe−Salpeter equation, we ab initio model both the Si L 2,3 and plasmon redshift. We find that the core-loss redshift occurs due to bandgap reduction from electron−phonon renormalization. Our results indicate that despite lower core-loss signal intensity compared to plasmon features, core-loss thermometry has key advantages and can be more accurate through standard spectral denoising. Specifically, we show that the Varshni equation easily interprets the core-loss redshift for semiconductors, which avoids plasmon spectral convolution for PEET in complex junctions and interfaces. We also find that core-loss thermometry is more accurate than PEET at modeling thermal lattice expansion in semiconductors, unless the specimen’s temperature-dependent dielectric properties are fully characterized. Furthermore, core-loss thermometry has the potential to measure nanoscale heating in multicomponent materials and stacked interfaces with elemental specificity at length scales smaller than the plasmon’s wave function.

Bethe–Salpeter equation↗
DOE OSTI2021

An overview of wind-energy-production prediction bias, losses, and uncertainties

Abstract. The financing of a wind farm directly relates to the preconstruction energy yield assessments which estimate the annual energy production for the farm. The accuracy and the precision of the preconstruction energy estimates can dictate the profitability of the wind project. Historically, the wind industry tended to overpredict the annual energy production of wind farms. Experts have been dedicated to eliminating such prediction errors in the past decade, and recently the reported average energy prediction bias is declining. Herein, we present a literature review of the energy yield assessment errors across the global wind energy industry. We identify a long-term trend of reduction in the overprediction bias, whereas the uncertainty associated with the prediction error is prominent. We also summarize the recent advancements of the wind resource assessment process that justify the bias reduction, including improvements in modeling and measurement techniques. Additionally, because the energy losses and uncertainties substantially influence the prediction error, we document and examine the estimated and observed loss and uncertainty values from the literature, according to the proposed framework in the International Electrotechnical Commission 61400-15 wind resource assessment standard. From our findings, we highlight opportunities for the industry to move forward, such as the validation and reduction of prediction uncertainty and the prevention of energy losses caused by wake effect and environmental events. Overall, this study provides a summary of how the wind energy industry has been quantifying and reducing prediction errors, energy losses, and production uncertainties. Finally, for this work to be as reproducible as possible, we include all of the data used in the analysis in appendices to the article.

17 WIND ENERGY↗
NASA NTRS2001

Turbo code carrier synchronization losses (Radio Losses)

In this paper the radio loss results for (8920,1/3), (8920,1/6), (1783,1/3) and (1784,1/6) codes are presented. These radio losses were calculated through simulations for a range of data rates. These simulations included both suppressed carrier modulation and residual carrier modulation cases. The radio losses were calculated for a frame error rate of 3 x 10^-4 for (8920,1/3) and (8920,1/6) codes and 3 frame error rate of 6 x 10^-5 for (1764,1/3) and (1784,1/6) codes. The simulations for the residual carrier case were run for loop signal to noise ratios of 13dB, 15dB and 17dB with a loop bandwidth of 10Hz. The simulations for the suppressed carrier case were run for a loop of signal to noise ratio of 17dB. The results of these simulations indicate that the radio losses for turbo codes are low enough to warrant their use in deep space links (maximum of 1dB loss at 17dB loop signal to noise ratio for residual carrier and 1.3dB loss at 17dB loop signal to noise ratio for suppressed carrier at high data rates). Furthermore, these results indicate that by normalizing the radio losses for frame size, loop bandwidth and the loop signal to noise ratio, a single curve could be used for calculating the radio loss for any given data rate at any given loop signal to noise ratio.

suppressed carrier↗
DOE OSTI2022

Impact of the built, social, and food environment on long‐term weight loss within a behavioral weight loss intervention

Abstract Background Behavioral weight loss interventions can lead to an average weight loss of 5%–10% of initial body weight, however there is wide individual variability in treatment response. Although built, social, and community food environments can have potential direct and indirect influences on body weight (through their influence on physical activity and energy intake), these environmental factors are rarely considered as predictors of variation in weight loss. Objective Evaluate the association between built, social, and community food environments and changes in weight, moderate‐to‐vigorous physical activity (MVPA), and dietary intake among adults who completed an 18‐month behavioral weight loss intervention. Methods Participants included 93 adults (mean ± SD; 41.5 ± 8.3 years, 34.4 ± 4.2 kg/m 2 , 82% female, 75% white). Environmental variables included urbanicity, walkability, crime, Neighborhood Deprivation Index (includes 13 social economic status factors), and density of convenience stores, grocery stores, and limited‐service restaurants at the tract level. Linear regressions examined associations between environment and changes in body weight, waist circumference (WC), MVPA (SenseWear device), and dietary intake (3‐day diet records) from baseline to 18 months. Results Grocery store density was inversely associated with change in weight ( β = −0.95; p = 0.02; R 2 = 0.062) and WC ( β = −1.23; p < 0.01; R 2 = 0.109). Participants living in tracts with lower walkability demonstrated lower baseline MVPA and greater increases in MVPA versus participants with higher walkability (interaction p = 0.03). Participants living in tracts with the most deprivation demonstrated greater increases in average daily steps ( β = 2048.27; p = 0.02; R 2 = 0.039) versus participants with the least deprivation. Limited‐service restaurant density was associated with change in % protein intake ( β = 0.39; p = 0.046; R 2 = 0.051). Conclusion Environmental factors accounted for some of the variability (<11%) in response to a behavioral weight loss intervention. Grocery store density was positively associated with weight loss at 18 months. Additional studies and/or pooled analyses, encompassing greater environmental variation, are required to further evaluate whether environment contributes to weight loss variability.

Tewahade, Selam↗
DOE OSTI2020

Machine Learning Methods for Connection RTT and Loss Rate Estimation Using MPI Measurements Under Random Losses

Scientific computations are expected to be increasingly distributed across wide-area networks, and Message Passing Interface (MPI) has been shown to scale to support their communications over long distances. Application-level measurements of MPI operations reflect the connection Round-Trip Time (RTT) and loss rate, and machine learningmethods have been previously developed to estimate them under deterministic periodic losses. In this paper, we consider more complex, random losses with uniform, Poisson and Gaussian distributions. We study five disparate machine leaning methods, with linear and non-linear, and smooth and non-smooth properties, to estimate RTT and loss rate over 10 Gbps connections with 0–366 ms RTT. The diversity and complexity of these estimators combined with the randomness of losses and TCP’s non-linear response together rule out the selection of a single best among them; instead, we fuse them to retain their design diversity. Overall, the results show that accurate estimates can be generated at low loss ratesbut become inaccurate at loss rates 10% and higher, thereby illustrating both their strengths and limitations.

Rao, Nageswara S.↗
DOE OSTI2024

Understanding Line Losses and Transformer Losses in Rural Isolated Distribution Systems: Preprint

Rural, isolated power systems in the mainland U.S. and in states like Alaska and Hawaii are powered by assets like diesel generators. These rural, isolated power systems also cannot operate at the higher band of medium voltage (like 69kV). They are primarily in the 12 to 14 kV range to keep the cost of the distribution investments lower. Because of this mid-band medium voltage range, the line losses and distribution transformers losses consume significant diesel consumption (almost 10 percent of the peak load). This work considers one such power system powering an isolated system and presents key findings online losses, and transformer losses. Understanding and documenting the impacts is critical for these communities operating their power systems and take actions to reduce expensive diesel consumption. In this paper, we will present one such typical grid and model it in electromagnetic transients (EMT) domain. We used the tower structure, under ground cabling installation to develop high fidelity models of lines. We also used high fidelity models of distribution transformers to present the no-load losses and full load loses. We will also present technical solutions available commercially off-the-shelf to reduce these losses and reduce diesel consumption. This work will be a primer for communities to understand the technical challenges and to understand the possible solution available to solve such challenges for rural, isolated power system operators.

blackstart↗
DOE OSTI2022

Failure diagnosis and trend‐based performance losses routines for the detection and classification of incidents in large‐scale photovoltaic systems

Abstract Fault detection and classification in photovoltaic (PV) systems through real‐time monitoring is a fundamental task that ensures quality of operation and significantly improves the performance and reliability of operating systems. Different statistical and comparative approaches have already been proposed in the literature for fault detection; however, accurate classification of fault and loss incidents based on PV performance time series remains a key challenge. Failure diagnosis and trend‐based performance loss routines were developed in this work for detecting PV underperformance and accurately identifying the different fault types and loss mechanisms. The proposed routines focus mainly on the differentiation of failures (e.g., inverter faults) from irreversible (e.g., degradation) and reversible (e.g., snow and soiling) performance loss factors based on statistical analysis. The proposed routines were benchmarked using historical inverter data obtained from a 1.8 MWp PV power plant. The results demonstrated the effectiveness of the routines for detecting failures and loss mechanisms and the capability of the pipeline for distinguishing underperformance issues using anomaly detection and change‐point (CP) models. Finally, a CP model was used to extract significant changes in time series data, to detect soiling and cleaning events and to estimate both the performance loss and degradation rates of fielded PV systems.

14 SOLAR ENERGY↗
DOE OSTI2021

Optical and Electronic Losses Arising from Physically Mixed Interfacial Layers in Perovskite Solar Cells

Perovskite solar cell device performance is affected by optical and electronic losses. To minimize these losses in solar cells, it is important to identify their sources. Here, we report the optical and electronic losses arising from physically mixed interfacial layers between the adjacent component materials in highly efficient two terminal (2T) all-perovskite tandem, single junction wide-bandgap, and single junction narrow-bandgap perovskite-based solar cells. Physically mixed interfacial layers as the sources of optical and electronic losses are identified from spectroscopic ellipsometry measurements and data analysis followed by comparisons of simulated and measured external quantum efficiency spectra. Parasitic absorbance in the physically mixed regions between silver metal electrical contacts and electron transport layers (ETLs) near the back contact and a physical mixture of commercial indium tin oxide and hole transport layers (HTL) near the front electrical contact lead to substantial optical loss. Here, a lower-density void + perovskite nucleation layer formed during perovskite deposition at the interface between the perovskite absorber layer and the HTL causes electronic losses due to incomplete collection of photogenerated carriers likely originating from poor coverage and passivation of the initially nucleating grains.

14 SOLAR ENERGY↗
DOE OSTI2022

Electron energy loss spectroscopy database synthesis and automation of core-loss edge recognition by deep-learning neural networks

Abstract The ionization edges encoded in the electron energy loss spectroscopy (EELS) spectra enable advanced material analysis including composition analyses and elemental quantifications. The development of the parallel EELS instrument and fast, sensitive detectors have greatly improved the acquisition speed of EELS spectra. However, the traditional way of core-loss edge recognition is experience based and human labor dependent, which limits the processing speed. So far, the low signal–noise ratio and the low jump ratio of the core-loss edges on the raw EELS spectra have been challenging for the automation of edge recognition. In this work, a convolutional-bidirectional long short-term memory neural network (CNN-BiLSTM) is proposed to automate the detection and elemental identification of core-loss edges from raw spectra. An EELS spectral database is synthesized by using our forward model to assist in the training and validation of the neural network. To make the synthesized spectra resemble the real spectra, we collected a large library of experimentally acquired EELS core edges. In synthesize the training library, the edges are modeled by fitting the multi-Gaussian model to the real edges from experiments, and the noise and instrumental imperfectness are simulated and added. The well-trained CNN-BiLSTM network is tested against both the simulated spectra and real spectra collected from experiments. The high accuracy of the network, 94.9%, proves that, without complicated preprocessing of the raw spectra, the proposed CNN-BiLSTM network achieves the automation of core-loss edge recognition for EELS spectra with high accuracy.

36 MATERIALS SCIENCE↗
DOE OSTI2023

Multiple mechanisms explain loss of anthocyanins from betalain‐pigmented Caryophyllales, including repeated wholesale loss of a key anthocyanidin synthesis enzyme

Summary In this study, we investigate the genetic mechanisms responsible for the loss of anthocyanins in betalain‐pigmented Caryophyllales, considering our hypothesis of multiple transitions to betalain pigmentation. Utilizing transcriptomic and genomic datasets across 357 species and 31 families, we scrutinize 18 flavonoid pathway genes and six regulatory genes spanning four transitions to betalain pigmentation. We examined evidence for hypotheses of wholesale gene loss, modified gene function, altered gene expression, and degeneration of the MBW (MYB‐bHLH‐WD40) trasnscription factor complex, within betalain‐pigmented lineages. Our analyses reveal that most flavonoid synthesis genes remain conserved in betalain‐pigmented lineages, with the notable exception of TT19 orthologs, essential for the final step in anthocyanidin synthesis, which appear to have been repeatedly and entirely lost. Additional late‐stage flavonoid pathway genes upstream of TT19 also manifest strikingly reduced expression in betalain‐pigmented species. Additionally, we find repeated loss and alteration in the MBW transcription complex essential for canonical anthocyanin synthesis. Consequently, the loss and exclusion of anthocyanins in betalain‐pigmented species appear to be orchestrated through several mechanisms: loss of a key enzyme, downregulation of synthesis genes, and degeneration of regulatory complexes. These changes have occurred iteratively in Caryophyllales, often coinciding with evolutionary transitions to betalain pigmentation.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2019

Quantifying Photocurrent Loss of a Single Particle–Particle Interface in Nanostructured Photoelectrodes

Particle–particle interfaces are ubiquitous in nanostructured photoelectrodes and photovoltaics, which are important devices for solar energy conversion. Furthermore, these interfaces are expected to cause performance losses in these devices, but how much loss they would incur is poorly defined. Here we use a subparticle photoelectrochemical current measurement, in combination with specific photoelectrode configurations, to quantify the current losses from single particle–particle interfaces formed between individual TiO 2 nanorods operating as photoanodes in aqueous electrolytes. We find that a single interface leads to ~20% photocurrent loss (i.e., ~80% retention of the original current). Such quantitative, first-of-its-kind, information provides a metric for guiding the optimization and design of nanostructured photoelectrodes and photovoltaics.

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

Low-loss single-photon NbN microwave resonators on Si

We present coplanar waveguide (CPW) microwave resonators with exceptionally low loss produced from NbN sputtered on Si. The NbN films are deposited with a modest RF substrate bias during reactive DC magnetron sputtering at a substrate temperature of 250 °C and can achieve a critical temperature as high as 15 K depending on the N2 flow rate. We measure the internal quality factors (Qi) of two such resonators at high-powers near saturation and report high-power quality factors in excess of 1.2 × 106 at 200 mK and 3.5 × 105 at 2 K. We also measure the temperature-dependent frequency shift at high power levels and the quality factor at single-photon power levels. From these measurements, we find a low-power (average photon number less than one) Qi value of 4.2 × 105 at 200 mK, which is consistent with a system limited by two-level-system loss.

Carter, Faustin W. (ORCID:0000000212363517)↗
DOE OSTI2020

Improvements to the Faraday cup fast ion loss detector and magnetohydrodynamic induced fast ion loss measurements in Joint European Torus plasmas

Upgrades to electronic hardware and detector design have been made to the JET thin-foil Faraday cup fast ion loss detector in anticipation of the upcoming deuterium–tritium (DT) campaign. An improved foil stack design has been implemented, which greatly reduces the number of foil-to-foil shorts, and triaxial cabling has mitigated ambient noise pickup. Initial tests of 200 kHz digitizers, as opposed to the original 5 kHz digitizers, have provided enhanced analysis techniques and direct coherence measurements of fast ion losses with magnetohydrodynamic activity. Here, we present recent loss measurements in JET deuterium plasmas correlated with kink modes, fishbone modes, edge-localized modes, and sawteeth. Sources of systematic noise are discussed with emphasis on capacitive plasma pickup. Overall, the system upgrades have established a diagnostic capable of recording alpha particle losses due to a wide variety of resonant fast ion transport mechanisms to be used in future DT-experiments and modeling efforts.

47 OTHER INSTRUMENTATION↗