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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 OSTI2021

Behavioral state resource selection in invasive wild pigs in the Southeastern United States

Elucidating correlations between wild pig ( Sus scrofa ) behavior and landscape attributes can aid in the advancement of management strategies for controlling populations. Using GPS data from 49 wild pigs in the southeastern U.S., we used hidden Markov models to define movement path characteristics and assign behaviors (e.g., resting, foraging, travelling). We then explored the connection between these behaviors and resource selection for both sexes between two distinct seasons based on forage availability (i.e., low forage, high forage). Females demonstrated a crepuscular activity pattern in the high-forage season and a variable pattern in the low-forage season, while males exhibited nocturnal activity patterns across both seasons. Wild pigs selected for bottomland hardwoods and dense canopy cover in all behavioral states in both seasons. Males selected for diversity in vegetation types while foraging in the low-forage season compared to the high-forage season and demonstrated an increased use of linear anthropogenic features across seasons while traveling. Wild pigs can establish populations and home ranges in an array of landscapes, but our results demonstrate male and female pigs exhibit clear differences in movement behavior and there are key resources associated with common behaviors that can be targeted to improve the efficiency of management programs.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2024

Enhancing the cooling performance of thermocouples: a power-constrained topology optimization procedure

Abstract Heat pumping through thermoelectric devices has many advantages over traditional cooling. However, their current efficiency is a limiting factor in their implementation. In this paper, we approach the non-convex topology optimization of thermoelectrical elements for cooling applications through the method of moving asymptotes (MMA) to improve their cooling capabilities per watt usage. The optimization problem is defined for a given power budget, aiming for the minimum temperature with a known heat pumping need. The introduction of power as a constraint justifies the introduction of the voltage gradient across the thermocouple as a design variable to maintain the thermoelectrical device in its optimum power-to-heat extraction ratio. To better understand the convergence of this non-convex problem, we present a two-variable analytical thermoelectric optimization model. This example provides information on how to select the penalty parameters used to scale the three material coefficients involved in the problem to obtain lower objective values and better convergence using MMA. The analytical model shows the non-convexity of the problem and provides the recommendation to use penalization coefficients of the form $$p_k=p_{\sigma }>p_{\alpha }=1$$ p k = p σ > p α = 1 for the thermal conductivity, electrical conductivity, and Seebeck coefficients. We tested these penalization coefficients through optimizations of a model based on the 1MC10-031 commercial thermoelectric-cooler (TEC) using the finite element method (FEM). These penalization coefficients provided local minima without the need for volume constraints. With this procedure, we found designs that provided temperatures close to 10 degrees lower using 60% less semiconductor material volume compared to the initial design.

Gutiérrez, G. Reales↗
DOE OSTI2024

Energy performance evaluation of the ASHRAE Guideline 36 control and reinforcement learning–based control using field measurements

This study evaluates the energy performance of ASHRAE Guideline 36–compliant control (ASHRAE 36 control) and reinforcement learning (RL)–based control through experimental field tests and a simulation study. Three field tests were conducted at Oak Ridge National Laboratory’s commercial building test facility in Oak Ridge, Tennessee: a baseline with a baseline conventional control, a test with ASHRAE 36 control, and a test with RL-based control. The selected ASHRAE 36 controls were trim and respond control, as well as variable air volume (VAV) box control. We compared the measured supply air temperature of the rooftop unit, VAV box supply air temperature, and VAV box supply airflow rate across the three test cases. The field data indicated that ASHRAE 36 controls operated as specified by ASHRAE Guideline 36. Based on these data, ASHRAE 36 control achieved a 45 % reduction in hourly averaged HVAC energy consumption compared with the baseline, and RL-based control achieved a 66 % reduction. These potential annual energy savings were confirmed using a calibrated whole-building energy model. Compared with the baseline, ASHRAE 36 control reduced HVAC energy consumption by 42 %, and RL-based control achieved a 54 % reduction. Furthermore, RL-based control reduced total HVAC energy consumption by 21 % more than ASHRAE 36 control.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗
DOE OSTI2024

Relating Molecular Properties to the Persistence of Marine Dissolved Organic Matter with Liquid Chromatography–Ultrahigh-Resolution Mass Spectrometry

Marine dissolved organic matter (DOM) contains a complex mixture of small molecules that eludes rapid biological degradation. Spatial and temporal variations in the abundance of DOM reflect the existence of fractions that are removed from the ocean over different time scales, ranging from seconds to millennia. However, it remains unknown whether the intrinsic chemical properties of these organic components relate to their persistence. Here, we elucidate and compare the molecular compositions of distinct DOM fractions with different lability along a water column in the North Atlantic Gyre. Our analysis utilized ultrahigh-resolution Fourier transform ion cyclotron resonance mass spectrometry at 21 T coupled to liquid chromatography and a novel data pipeline developed in CoreMS that generates molecular formula assignments and metrics of isomeric complexity. Clustering analysis binned 14 857 distinct molecular components into groups that correspond to the depth distribution of semilabile, semirefractory, and refractory fractions of DOM. The more labile fractions were concentrated near the ocean surface and contained more aliphatic, hydrophobic, and reduced molecules than the refractory fraction, which occurred uniformly throughout the water column. These findings suggest that processes that selectively remove hydrophobic compounds, such as aggregation and particle sorption, contribute to variable removal rates of marine DOM.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2022

Time-Evolving Chirality Loss in Molecular Photodissociation Monitored by X-ray Circular Dichroism Spectroscopy

In this work, the ultrafast photoinduced chirality loss of 2-iodobutane is studied theoretically by time- and frequency-resolved X-ray circular dichroism (TRXCD) spectroscopy. Following an optical excitation, the iodine atom dissociates from the chiral center, which we capture by quantum non-adiabatic molecular dynamics simulations. At variable time delays after the pump, the resonant X-ray pulse selectively probes the iodine and carbon atom involved in the chiral dissociation through a selected core-to-valence transition. The TRXCD signal at the iodine L 1 edge accurately captures the timing of C–I photodissociation and thereby chirality loss, c.a 70 fs. The strong electric dipole–electric quadrupole (ED–EQ) response makes this signal particularly sensitive to vibronic coherence at the high X-ray regime. At the carbon K-edges, the signals monitor the molecular chirality of the 2-butyl radical photoproduct and the spin state of the iodine atom. The ED–EQ response is masked under the strong electric dipole-magnetic dipole response, making this signal intuitive for the electronic population. The evolution of the core electronic states and its chiral sensitivity is discussed. Overall, the element-specific TRXCD signal provides a detailed picture of molecular dynamics and offers a unique sensitive window into the time-dependent chirality of molecules.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2025

Conductivity space isotherm behavior in quantum anomalous Hall devices

The quantum Hall effect (QHE) has enhanced accessibility to measure and disseminate electrical units, owed in part to the recently redefined International System of Units in 2019. Graphene remains one of the preferred options to realize the ohm despite the limitations of high magnetic fields to produce a robust QHE. Topological insulators, on the other hand, show promise in providing quantized resistance via the quantum anomalous Hall effect, a phenomenon that removes the need for magnetic fields during operation. To optimize future devices for metrological applications, it is important to gain a better understanding of magnetically doped topological insulators like Cr-doped bismuth antimony telluride. The application of differential conductivity space analyses offers a more sensitive way to analyze the data and distinguish between 2D and 3D transport behaviors. This is particularly important in thin films, where the transition between 2D and 3D behavior can be subtle. The ability to confidently determine the dimensionality of the transport is crucial for selecting appropriate theoretical models for future device optimization. Furthermore, this work identifies variable range hopping as the dominant transport mechanism in the 2D regime using a rigorous statistical analysis (via the Bayes factor). These elements assist in the understanding of microscopic processes that govern charge transport in these materials.

Tran, N. T. M. [National Inst. of Standards and Te↗
DOE OSTI2021

A Novel Variable Extensometer Method for Measuring Ductility Scaling Parameters From Single Specimens

Abstract Macro-scale ductility is not an intrinsic material property but is dependent on the overall geometry of the specimen. To account for variety in specimen geometries, multiple ductility scaling laws have been developed, which scale ductility between different specimen sizes. Traditionally, these ductility laws rely on testing multiple different specimens of varying sizes to obtain material parameters, often done by varying gauge lengths. With the use of digital image correlation (DIC), this study presents a technique where multiple different gauge lengths are extracted from a single specimen to obtain ductility scaling parameters from a single experiment. This technique provides orders of magnitude more data from each specimen than previous techniques. This variable extensometer method is then validated by testing multiple different geometries, and select scaling laws are then compared.

Mechanics↗
DOE OSTI2023

Electrochemical Characteristics of Intermetallic Phases in Al–Cu–Li Alloys

This study provides a comprehensive overview of the electrochemical characteristics of intermetallic compounds (IMCs) commonly encountered in the 3rd generation Al–Cu–Li alloys. The electrochemical measurements were carried out on a AA2070-T8 alloy and surrogate alloys that have the compositions of select IMCs, typically found in AA2070-T8. The effects of environmental variables such as [Cl − ] and pH on the corrosion potential, pitting potential, repassivation potential, corrosion rate, and galvanic current of these IMCs were thoroughly evaluated utilizing the electrochemical microcell method. An electrochemical database was documented that covers eight groups of common IMCs in various Al alloys. The findings improve the understanding of interactions between matrix and IMCs in Al alloys, with implications for corrosion mitigation and new materials design.

36 MATERIALS SCIENCE↗
DOE OSTI2021

Single Photon Emitters Coupled to Photonic Wire bonds

This project will test the coupling of light emitted from silicon vacancy and nitrogen vacancy defects in diamond into additively manufactured photonic wire bonds toward integration into an "on-chip quantum photonics platform". These defects offer a room-temperature solid state solution for quantum information technologies but suffer from issues such as low activation rate and variable local environments. Photonic wire bonding will allow entanglement of pre-selected solid-state defects alleviating some of these issues and enable simplified integration with other photonic devices. These developments could prove to be key technologies to realize quantum secured networks for national security applications.

42 ENGINEERING↗
DOE OSTI2024

Innovating the next generation of commercial smart building software

Nearly 30% of commercial building energy use is wasted due to equipment faults and HVAC controls problems. The result is increased emissions, compromised comfort and productivity, and less reliable coordination of building power needs with a clean grid. The energy impact alone represents $17 billion in potential savings. Today’s smart building software provides a robust solution to address these operational deficiencies. Energy management and information systems (EMIS) are saving up to 9% on average, with two-year paybacks. They are being incorporated into energy management processes, commissioning services, and utility programs. As effective as they are, two barriers prevent even deeper benefits; limited personnel to fix problems once they are identified, and the expense and time to manually implement changes in control systems. In partnership with the research community, the EMIS industry is developing new capabilities to overcome these barriers. Moving beyond siloed products for either fault detection and diagnostics, or optimal control, these new capabilities empower users to not only automatically identify faults, but also to push corrective action, and control improvements to their buildings. In this paper, several areas for enhancements are documented: ‘one-time’ correction of faults such as setpoints, schedules, and economizer lockouts; short-term active testing for automated proportional integral derivative (PID) loop tuning and functional testing; and continuous supervisory control for demand flexibility and year-round efficiency. Results are presented from a pair of partner implementations out of a dozen providers integrating these enhancements into their products, including field tests from across the country, and insights into operator acceptance and integration into operations and maintenance practices.

Casillas, Armando↗
DOE OSTI2021

Data-driven estimation of energy consumption for electric bus under real-world driving conditions

Reliable and accurate estimation of an electric bus’s instantaneous energy consumption is critical in evaluating energy impacts of planning and control of electric bus operations. In this study, we developed machine learning-based long short-term memory (LSTM) and artificial neural network (ANN) models to estimate 1 Hz energy consumption of electric buses based on continuous monitoring data of electric buses in Chattanooga, Tennessee, in 2019 and 2020. We propose a data-partitioning algorithm to separate energy charging and discharging modes before applying data-driven estimation models. Here, a K-fold cross-validation-based model selection process was conducted to identify the optimal model structure and input variables in terms of prediction accuracy. The estimation results show the predicted mean absolute percentage error rates of LSTM and ANN models were 3% and 5%, respectively. We compared the proposed models with existing models in the literature based on the same testing data to demonstrate the predictability of our models.

Artificial neural network↗
DOE OSTI2024

Investigating the impacts of solid phase extraction on dissolved organic matter optical signatures and the pairing with high‐resolution mass spectrometry data across a freshwater stream network

Abstract Advancing our understanding of dissolved organic matter (DOM) chemistry in aquatic systems necessitates the integration of data streams from multiple analytical platforms. Some measurements require pretreatment with solid phase extraction (SPE), while others are performed directly on whole water samples. Evidence has suggested that SPE will be biased against select DOM fractions, leading to concerns over the ability to establish data linkages across platforms with variable needs for SPE pretreatment, such as those from optical measurements and those that provide high‐resolution molecular information. Here, we directly addressed this concern by assessing the impact of SPE on DOM optical properties through excitation–emission matrices with parallel factor analysis (PARAFAC) for 47 samples across a stream network within a single watershed reflective of variable DOM sources. PARAFAC data was further paired with molecular information obtained by Fourier transform ion cyclotron resonance mass spectrometry (FTICR‐MS). A comparison of PARAFAC models first revealed no systematic qualitative differences in major components between whole water DOM and DOM isolated by SPE (SPE‐DOM); however, quantitative biases against select components were observed. Further linkages with FTICR‐MS data revealed that the molecular fingerprint associated with each PARAFAC component was consistent between the whole water DOM and SPE‐DOM. Our results suggest that bulk scale linkages across these analytical platforms could be inferred irrespective of the observed quantitative biases resulting from SPE for samples within this example watershed. This work represents a key step toward the systematic evaluation of linkages between optical and high‐resolution mass spectrometry datasets in freshwater lotic environments.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2026

Measurements of $\textrm{t}\overline{\textrm{t}}\textrm{W}$ differential cross sections and the leptonic charge asymmetry at $\sqrt{s}=13$ TeV

Measurements of properties of top quark-antiquark pair production in association with a W boson in proton-proton collisions at a center-of-mass energy of 13 TeV are presented, using a data sample corresponding to an integrated luminosity of 138 fb −1 , recorded by the CMS experiment at the CERN LHC. Events are selected based on the presence of either two leptons with the same electric charge or three leptons, and multiple jets and b-tagged jets. We present measurements of differential production cross sections as a function of kinematic variables sensitive to different aspects of the process modeling, using a multivariate discriminator in the two-lepton selection region and a simple selection-based method in the three-lepton region. The normalized cross section measurements are generally consistent with the standard model expectations, while we observe larger values compared to the expectations in the absolute cross section measurements, consistent with previous inclusive cross section measurements. In addition, we measure the leptonic charge asymmetry of this process, obtaining an observed value of ${A}_c^{\ell }=-{0.19}_{-0.18}^{+0.16}$, consistent with the expectation of −0.085 ± 0.006 predicted by next-to-leading order simulations.

Hadron-Hadron Scattering↗
DOE OSTI2023

Earth System Model Aerosol–Cloud Diagnostics (ESMAC Diags) package, version 2: assessing aerosols, clouds, and aerosol–cloud interactions via field campaign and long-term observations

Abstract. Poor representations of aerosols, clouds, and aerosol–cloud interactions (ACIs) in Earth system models (ESMs) have long been the largest uncertainties in predicting global climate change. Huge efforts have been made to improve the representation of these processes in ESMs, and the key to these efforts is the evaluation of ESM simulations with observations. Most well-established ESM diagnostics packages focus on the climatological features; however, they lack process-level understanding and representations of aerosols, clouds, and ACIs. In this study, we developed the Earth System Model Aerosol–Cloud Diagnostics (ESMAC Diags) package to facilitate the routine evaluation of aerosols, clouds, and ACIs simulated the Energy Exascale Earth System Model (E3SM) from the US Department of Energy (DOE). This paper documents its version 2 functionality (ESMAC Diags v2), which has substantial updates compared with version 1 (Tang et al., 2022a). The simulated aerosol and cloud properties have been extensively compared with in situ and remote-sensing measurements from aircraft, ship, surface, and satellite platforms in ESMAC Diags v2. It currently includes six field campaigns and two permanent sites covering four geographical regions: the eastern North Atlantic, the central US, the northeastern Pacific, and the Southern Ocean. These regions produce frequent liquid- or mixed-phase clouds, with extensive measurements available from the DOE Atmospheric Radiation Measurement user facility and other agencies. ESMAC Diags v2 generates various types of single-variable and multivariable diagnostics, including percentiles, histograms, joint histograms, and heatmaps, to evaluate the model representation of aerosols, clouds, and ACIs. Select examples highlighting the capabilities of ESMAC Diags are shown using E3SM version 2 (E3SMv2). In general, E3SMv2 can reasonably reproduce many observed aerosol and cloud properties, with biases in some variables such as aerosol particle and cloud droplet sizes and number concentrations. The coupling of aerosol and cloud number concentrations may be too strong in E3SMv2, possibly indicating a bias in processes that control aerosol activation. Furthermore, the liquid water path response to a perturbed cloud droplet number concentration behaves differently in E3SMv2 and observations, which warrants further study to improve the cloud microphysics parameterizations in E3SMv2.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2023

Do people spend travel time the way they think they would? a comparative study of generic and trip-specific travel time allocation using hybrid multiple discrete continuous (MDC) framework

Unlike driving alone, public transportation allows one to engage in extraneous activities while traveling – often referred to as travel-based multitasking. Research involving travel-based multitasking often relies on either generic (i.e. not related to an actual trip) or revealed (i.e. related to an executed trip) data. The data collected for this study provided a unique opportunity to compare the generic and trip-specific preferences while traveling on public transportation. To this end, the study develops two integrated choice and latent variable models with multiple discrete-continuous (MDC) kernels to simultaneously model the activity selection and the time allocation for generic and trip-specific data, respectively. According to the results the trip-specific data could identify more nuances in the travel-based multitasking behavior than the generic data. Finally, the heterogeneity identified by the developed models will be helpful for the transit operators in providing appropriate facilities (e.g. internet access, reading lights) along various transit corridors.

99 GENERAL AND MISCELLANEOUS↗
DOE OSTI2021

Iterative self-organizing SCEne-LEvel sampling (ISOSCELES) for large-scale building extraction

Convolutional neural networks (CNN) provide state-of-the-art performance in many computer vision tasks, including those related to remote-sensing image analysis. Successfully training a CNN to generalize well to unseen data, however, requires training on samples that represent the full distribution of variation of both the target classes and their surrounding contexts. With remote sensing data, acquiring a sufficiently representative training set is a challenge due to both the inherent multi-modal variability of satellite or aerial imagery and the general high cost of labeling data. To address this challenge, we have developed ISOSCELES, an Iterative Self-Organizing SCEne LEvel Sampling method for hierarchical sampling of large image sets. Using affinity propagation, ISOSCELES automates the selection of highly representative training images. Compared to random sampling or using available reference data, the distribution of the training is principally data driven, reducing the chance of oversampling uninformative areas or undersampling informative ones. In comparison to manual sample selection by an analyst, ISOSCELES exploits descriptive features, spectral and/or textural, and eliminates human bias in sample selection. Using a hierarchical sampling approach, ISOSCELES can obtain a training set that reflects both between-scene variability, such as in viewing angle and time of day, and within-scene variability at the level of individual training samples. We verify the method by demonstrating its superiority to stratified random sampling in the challenging task of adapting a pre-trained model to a new image and spatial domain for country-scale building extraction. Using a pair of hand-labeled training sets comprising 1,987 sample image chips, a total of 496,000,000 individually labeled pixels, we show, across three distinct model architectures, an increase in accuracy, as measured by F1-score, of 2.2–4.2%.

42 ENGINEERING↗
DOE OSTI2025

Environmental Metrics of Ethanol Production Improve with Increased Biomass Yield and Carbohydrate Content in Populus Trichocarpa

When selecting economically and environmentally advantageous genotypes for domestication in a biofuel supply chain, variability of cell-wall composition within a feedstock population and its impact on biorefinery metrics must be understood. We performed a life cycle assessment (LCA) on a poplar-to-ethanol supply chain to quantify global warming potential and cumulative energy demand as affected by variable carbohydrate content in a large representative natural variant population of Populus trichocarpa. The results showed that both environmental metrics decrease with increasing tree size and with increasing biomass carbohydrate content. These trends parallel prior economic results and provide clear direction to breeders or genetic engineers when improving poplar cultivars.

09 BIOMASS FUELS↗
DOE OSTI2022

Local Structure Analysis and Modelling of Lignin‐Based Carbon Composites through the Hierarchical Decomposition of the Radial Distribution Function

Abstract Carbonized lignin has been proposed as a sustainable and domestic source of activated, amorphous, graphitic, and nanostructured carbon for many industrial applications as the structure can be tuned through processing conditions. However, the inherent variability of lignin and its complex physicochemical structure resulting from feedstock and pulping selection make the Process‐Structure‐Property‐Performance (PSPP) relationships hard to define. In this work, radial distribution functions (RDFs) from synchrotron X‐ray and neutron scattering of lignin‐based carbon composites (LBCCs) are investigated using the Hierarchical Decomposition of the Radial Distribution Function (HDRDF) modelling method to characterize the local atomic environment and develop quantitative PSPP relationships. PSPP relationships for LBCCs defined by this work include crystallite size dependence on lignin feedstock as well as increasing crystalline volume fraction, nanoscale composite density, and crystallite size with increasing reduction temperature.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗