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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 127 records · Page 7
All sourcesNASA NTRSDOE OSTI
DOE OSTI2024

Frequency Nadir Constrained Unit Commitment for High Renewable Penetration Island Power Systems

The process of energy decarbonization in island power systems is accelerated due to the swift integration of inverter-based renewable energy resources (IBRs). The unique features of such systems, including rapid frequency changes resulting from potential generation outages or imbalances due to the unpredictability of renewable power, pose a significant challenge in maintaining the frequency nadir without external support. This paper presents a unit commitment (UC) model with data-driven frequency nadir constraints, including either frequency nadir or minimum inertia requirements, helping to limit frequency deviations after significant generator outages. The constraints are formulated using a linear regression model that takes advantage of real-world, year-long generation scheduling and dynamic simulation data. The efficacy of the proposed UC model is verified through a year-long simulation in an actual island power system using historical weather data. The alternative minimum inertia constraint, derived from actual system operation assumptions, is also evaluated. Findings demonstrate that the proposed frequency nadir constraint notably improves the system's frequency nadir under high photovoltaic (PV) penetration levels, albeit with a slight increase in generation costs, when compared to the alternative minimum inertia constraint.

24 POWER TRANSMISSION AND DISTRIBUTION↗
DOE OSTI2023

The Influence of Strain Path and Heat Treatment Variations on Recrystallization in Cold-Rolled High-Purity Niobium Polycrystals

With the standard material and cavity production guidelines, the properties and performance of industrially produced high-purity niobium superconducting radiofrequency (SRF) cavities are unpredictably variable. Currently, assembled niobium SRF cavities undergo post-purification vacuum heat treatment at 800 °C for three hours to remove hydrogen and increase performance; however, recent work has shown significant improvements in cavity performance when annealed between 900–1000 °C, causing recrystallization (Rx). Increasing the annealing temperature and/or the heating rate should facilitate the onset of Rx, resulting in a greater reduction in the density of geometrically necessary dislocations (GNDs) that are strongly associated with the degradation of cavity performance via trapped magnetic flux. Improving the SRF community's understanding of the influence of both heat treatment and deformation history on the resulting microstructure and Rx behavior in high-purity niobium is needed. This fundamental metallurgy is critical for identifying improved specifications for the consistent production of high-performing niobium SRF cavities. This research investigates variations in deformation paths, heating rates, and annealing temperatures on Rx of deformed samples of polycrystalline high-purity niobium. To assess the effects of strain path, samples were cold-rolled to ~30% reduction prior to annealing, with half of the sample set rolled parallel to the as-received niobium sheet and the other half in the transverse direction.

36 MATERIALS SCIENCE↗
DOE OSTI2021

Pulsar Based Timing for Grid Synchronization

Existing synchronization systems in the power grid, such as the global positioning system, are susceptible to temporary or permanent failures due to various unpredictable and uncontrollable factors such as cyber-attack and electromagnetic interferences, thus affecting the accuracy and reliability of generated timing signal. In this article, a pulsar astronomy-based timing system is proposed to provide an alternative synchronization signal. Further, this clock will offer significant security improvements to power grid applications, such as a wide-area monitoring system, which depends on a precise timing signal. The hardware and software frameworks are described in detail. First, a high-speed sampling hardware platform is designed to collect signals from radio telescopes. Then a periodic pulse extraction method with three steps is proposed to process the pulsar signal, including polyphase filterbanks, incoherent de-dispersion, and sliding window folding. Lastly, three experiments are conducted to verify the effectiveness of the frameworks. The generated pulsar timing pulse is presented, and the factors affecting its accuracy are also discussed. The analysis results demonstrate that the pulsar signals can provide high-accurate timing pulses for grid synchronization.

24 POWER TRANSMISSION AND DISTRIBUTION↗
DOE OSTI2025

Enhancing ACPF Analysis: Integrating Newton-Raphson Method with Gradient Descent and Computational Graphs

This paper presents a new method for enhancing Alternating Current Power Flow (ACPF) analysis. The method integrates the Newton-Raphson (NR) method with Enhanced-Gradient Descent (GD) and computational graphs. The integration of renewable energy sources in power systems introduces variability and unpredictability, and this method addresses these challenges. It leverages the robustness of NR for accurate approximations and the flexibility of GD for handling variable conditions, all without requiring Jacobian matrix inversion. Furthermore, computational graphs provide a structured and visual framework that simplifies and systematizes the application of these methods. The goal of this fusion is to overcome the limitations of traditional ACPF methods and improve the resilience, adaptability, and efficiency of modern power grid analyses. We validate the effectiveness of our advanced algorithm through comprehensive testing on established IEEE benchmark systems. Furthermore, our findings demonstrate that our approach not only speeds up the convergence process but also ensures consistent performance across diverse system states, representing a significant advancement in power flow computation.

24 POWER TRANSMISSION AND DISTRIBUTION↗
DOE OSTI2022

Flow Loop Study of ECT-Based Volume Fraction Monitoring in Oil–Water Two-Phase Flows

Measurement of phase volume fractions in water-containing multiphase flows is necessary for the optimization of a host of industrial flow processes. Many water-containing multiphase flows can be classified as either water-dispersed or water-continuous mixtures. A recently developed approach based on Hanai’s mixture formula and utilizing electrical capacitance tomography (ECT) sensors have shown good potential for obtaining water volume fraction estimates in two-phase water-containing flows with different water salinity levels. However, the proposed approach was investigated via controlled experiments restricted to static configurations while, in practice, multiphase flows can be dynamic and unpredictable. In this work, we perform a flow loop study of the proposed ECT-based method for volume fraction estimation in oil–water two-phase flows. Here, we evaluate the performance of the proposed method in both water-dispersed and water-continuous flow regimes by employing different types of capacitive sensors in cylindrical arrangements and parallel-plate rectangular arrangements.

02 PETROLEUM↗
DOE OSTI2021

Event-Driven Predictive Approach for Real-Time Volt/VAR control with CVR in solar PV rich Active Distribution Network

The focus of this paper is on analyzing the impact of conservation voltage reduction in the presence of active devices such as solar photovoltaic (PV) and developing controls that leverage these distributed energy resources. An event-driven predictive approach for real-time volt/volt-ampere reactive (VAR) optimization, along with local two-level adaptive volt/VAR droop-based control algorithm for advanced distribution management systems, is introduced. The methodology covers aggregated and autonomous controls under different timescale operations, including the impact and effect of unpredicted events such as cloud transients on PV power production. In addition, the control schemes include the uncertainties in PV power generation and load power demand. The proposed methodology is validated in a real-time framework using the real-time digital simulator platform through co-simulation with models based on Python and OpenDSS (Open Distribution System Simulator). The developed methodology is tested on the modified IEEE 123-feeder test system. The results reveal that the proposed methodology works well in the presence of high penetrations of PV power, produces significant energy savings, and mitigates over-/undervoltage problems.

14 SOLAR ENERGY↗
DOE OSTI2020

Experimental testing of hypotheses for temperature‐ and pH ‐based niche specialization of ammonia oxidizing archaea and bacteria

Summary Investigation of niche specialization in microbial communities is important in assessing consequences of environmental change for ecosystem processes. Ammonia oxidizing bacteria (AOB) and archaea (AOA) present a convenient model for studying niche specialization. They coexist in most soils and effects of soil characteristics on their relative abundances have been studied extensively. This study integrated published information on the influence of temperature and pH on AOB and AOA into several hypotheses, generating predictions that were tested in soil microcosms. The influence of perturbations in temperature was determined in pH 4.5, 6 and 7.5 soils and perturbations in pH were investigated at 15°C, 25°C and 35°C. AO activities were determined by analysing changes in amoA gene and transcript abundances, stable isotope probing and nitrate production. Experimental data supported major predictions of the effects of temperature and pH, but with several significant discrepancies, some of which may have resulted from experimental limitations. The study also provided evidence for unpredicted activity of AOB in pH 4.5 soil. Other discrepancies highlighted important deficiencies in current knowledge, particularly lack of consideration of niche overlap and the need to consider combinations of factors when assessing the influence of environmental change on microbial communities and their activities.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2022

Correction and calibration of atmospheric impact observations in GOES GLM data

The Earth's atmosphere is impacted daily by both meteoroids and artificial objects. Calibrated observations of the emitted light at sufficiently high sampling rates can enable or improve the estimation of impactor attributes such as size, cohesion, trajectory, and composition, but are difficult to obtain owing to the unpredictability, brevity, and high dynamic (brightness) range of impacts. Ground-based camera systems have successfully monitored small regions of the atmosphere at video frame rates and with limited radiometric capabilities, but most impacts occur over the 70% of the Earth's surface covered by water and are therefore missed by these networks. The Geostationary Lightning Mapper (GLM) instruments aboard Geostationary Operational Environmental Satellites 16 and 17 provide near-hemispherical coverage at 500 frames per second. These data have been shown to contain the signatures of many independently confirmed impacts, often from both viewing angles simultaneously, and constitute an observational resource that is currently unparalleled in the public domain. NASA's Asteroid Threat Assessment Project has implemented an automated impact detection pipeline that processes data from GLM daily. Given a detected impact, the GLM data contain a wealth of information for use in quantitative follow-up analyses. However, impact events differ from lightning in ways that violate key assumptions built into GLM's design. The result is that GLM's onboard processing introduces errors into pixel observations of impact events and the calibrated energies near the periphery of the detector may be substantially overestimated. We present methods for mitigating these and other issues to produce a data product more suitable for impact analyses than the existing GLM lightning product.

58 GEOSCIENCES↗
DOE OSTI2021

Growth–defense trade‐offs and yield loss in plants with engineered cell walls

Summary As a major component of plant secondary cell walls, lignin provides structural integrity and rigidity, and contributes to primary defense by providing a physical barrier to pathogen ingress. Genetic modification of lignin biosynthesis has been adopted to reduce the recalcitrance of lignified cell walls to improve biofuel production, tree pulping properties and forage digestibility. However, lignin‐modification is often, but unpredictably, associated with dwarf phenotypes. Hypotheses suggested to explain this include: collapsed vessels leading to defects in water and solute transport; accumulation of molecule(s) that are inhibitory to plant growth or deficiency of metabolites that are critical for plant growth; activation of defense pathways linked to cell wall integrity sensing. However, there is still no commonly accepted underlying mechanism for the growth defects. Here, we discuss recent data on transcriptional reprogramming in plants with modified lignin content and their corresponding suppressor mutants, and evaluate growth‐defense trade‐offs as a factor underlying the growth phenotypes. New approaches will be necessary to estimate how gross changes in transcriptional reprogramming may quantitatively affect growth. Better understanding of the basis for yield drag following cell wall engineering is important for the biotechnological exploitation of plants as factories for fuels and chemicals.

Ha, Chan Man↗
DOE OSTI2023

Walking the ‘design–build–test–learn’ cycle: flux analysis and genetic engineering reveal the pliability of plant central metabolism

Oilseeds are of great economic importance for food and animal feed and their contribution to renewable energy production. Soybean seeds (Glycine max (L.) Merr.) contain c. 40% protein, 20% oil, and 30% carbohydrate (Song et al., 2023). Due to the massive scale of soybean production worldwide, even small improvements in seed protein and oil content make economic sense (Song et al., 2023). Successful manipulation of seed composition largely depends on a thorough understanding of the processes and pathways involved in the biosynthesis of fatty acids and amino acids, which are the building blocks of lipids and proteins. Rational engineering of the synthesis of storage reserves, that is, the rerouting of metabolic flux in central metabolism, is difficult to accomplish due to the complexity of the central metabolic network, the intricate regulation of its enzymes at multiple levels, and the often-unpredictable effects of genetic manipulation (Sweetlove et al., 2017). Therefore, the advancement of our understanding of central metabolism and its control of carbon partitioning requires following an iterative ‘design–build–test–learn’ (DBTL) cycle (Lin & Eudes, 2020) where metabolic flux analysis and hypothesis testing by transgenic approaches are important components. Previous metabolic studies on soybeans using isotopic tracers and metabolic flux analysis have provided insight into how lipid and protein biosynthesis occurs simultaneously during seed development (Allen et al., 2009; Allen & Young, 2013; Kambhampati et al., 2021). In an article published in this issue of New Phytologist, Morley et al. (2023; 1834–1851) put the insights they have gained into the delivery of metabolic precursors and energy cofactors to oil synthesis to the test and arrive at a successful metabolic engineering design. They show that an increase in seed oil content in soybeans can be achieved by overexpression of malic enzyme (ME) during seed development. Malic enzyme refers to a class of decarboxylating malate dehydrogenase enzymes that oxidize malate with NAD + or NADP + as redox cofactor while generating pyruvate and CO 2 . Like higher plants in general, soybean has distinct NADH- or NADPH-producing ME isoforms localized to the cytosol, plastid, or mitochondria (Gerrard Wheeler et al., 2016). As Morley et al. show, an increase in seed oil can be achieved in particular when a NADP+-dependent enzyme isoform (EC 1.1.1.40) is overexpressed in the plastid. Given the complex compartmentalization of pyruvate, malate, and redox metabolism (Fig. 1), increased oil production appears to depend on additional pyruvate and reducing equivalents being produced in the same compartment where de novo fatty acid biosynthesis occurs: the plastid.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2024

Inverse design of a pyrochlore lattice of DNA origami through model-driven experiments

Sophisticated statistical mechanics approaches and human intuition have demonstrated the possibility of self-assembling complex lattices or finite-size constructs. However, attempts so far have mostly only been successful in silico and often fail in experiment because of unpredicted traps associated with kinetic slowing down (gelation, glass transition) and competing ordered structures. Theoretical predictions also face the difficulty of encoding the desired interparticle interaction potential with the experimentally available nano- and micrometer-sized particles. To overcome these issues, we combine SAT assembly (a patchy-particle interaction design algorithm based on constrained optimization) with coarse-grained simulations of DNA nanotechnology to experimentally realize trap-free self-assembly pathways. In this paper, we use this approach to assemble a pyrochlore three-dimensional lattice, coveted for its promise in the construction of optical metamaterials, and characterize it with small-angle x-ray scattering and scanning electron microscopy visualization.

77 NANOSCIENCE AND NANOTECHNOLOGY↗
DOE OSTI2020

Effects of Genetic and Physiological Divergence on the Evolution of a Sulfate-Reducing Bacterium under Conditions of Elevated Temperature

ABSTRACT Adaptation via natural selection is an important driver of evolution, and repeatable adaptations of replicate populations, under conditions of a constant environment, have been extensively reported. However, isolated groups of populations in nature tend to harbor both genetic and physiological divergence due to multiple selective pressures that they have encountered. How this divergence affects adaptation of these populations to a new common environment remains unclear. To determine the impact of prior genetic and physiological divergence in shaping adaptive evolution to accommodate a new common environment, an experimental evolution study with the sulfate-reducing bacterium Desulfovibrio vulgaris Hildenborough (DvH) was conducted. Two groups of replicate populations with genetic and physiological divergence, derived from a previous evolution study, were propagated in an elevated-temperature environment for 1,000 generations. Ancestor populations without prior experimental evolution were also propagated in the same environment as a control. After 1,000 generations, all the populations had increased growth rates and all but one had greater fitness in the new environment than the ancestor population. Moreover, improvements in growth rate were moderately affected by the divergence in the starting populations, while changes in fitness were not significantly affected. The mutations acquired at the gene level in each group of populations were quite different, indicating that the observed phenotypic changes were achieved by evolutionary responses that differed between the groups. Overall, our work demonstrated that the initial differences in fitness between the starting populations were eliminated by adaptation and that phenotypic convergence was achieved by acquisition of mutations in different genes. IMPORTANCE Improving our understanding of how previous adaptation influences evolution has been a long-standing goal in evolutionary biology. Natural selection tends to drive populations to find similar adaptive solutions for the same selective conditions. However, variations in historical environments can lead to both physiological and genetic divergence that can make evolution unpredictable. Here, we assessed the influence of divergence on the evolution of a model sulfate-reducing bacterium, Desulfovibrio vulgaris Hildenborough, in response to elevated temperature and found a significant effect at the genetic but not the phenotypic level. Understanding how these influences drive evolution will allow us to better predict how bacteria will adapt to various ecological constraints.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2024

Divergence Reduction in Monte Carlo Neutron Transport with On-GPU Asynchronous Scheduling

While Monte Carlo Neutron Transport (MCNT) is near-embarrasingly parallel, the effectively unpredictable lifetime of neutrons can lead to divergence when MCNT is evaluated on GPUs. Divergence is the phenomenon of adjacent threads in a warp executing different control flow paths; on GPUS, it reduces performance because each work group may only execute one path at a time. The process of Thread Data Remapping (TDR) resolves these discrepancies by moving data across hardware such that data in the same warp will be processed through similar paths. A common issue among prior implementations of TDR is the synchronous nature of its remapping and processing cycles, which exhaustively sort data produced by prior processing passes and exhaustively evaluate the sorted data. In another work, we defined a method of remapping data through an asynchronous scheduler which allows for work to be stored in shared memory and deferred arbitrarily until that work is a viable option for low-divergence evaluation. This article surveys a wider set of cases, with the goal of characterizing performance trends across a more comprehensive set of parameters. These parameters include cross sections of scattering/capturing/fission, use of implicit capture, source neutron counts, simulation time spans, and tuned memory allocations. Across these cases, we have recorded minimum and average execution times, as well as a heuristically tuned near-optimal memory allocation size for both synchronous and asynchronous scheduling. Across the collected data, it is shown that the asynchronous method is faster and more memory efficient in the majority of cases, and that it requires less tuning to achieve competitive performance.

Computer Science↗
DOE OSTI2021

EMOS (Energy Management Optimization System) [SWR-21-46]

EMOS software performs a real-time hierarchal optimal control for energy systems like multi-port electric vehicles charging site with distributed energy resources (DERs) and energy storage systems (ESSs). It gathers information in real-time from electric vehicles, power grid, and DERs, solves a multi-objective energy management optimization problem, and output setpoint for chargers, ESS converters, DERs converters, and grid converters. The software incorporates a novel integration of two control tasks: a) An Energy Management Optimization (EMO), which is the brain of EMOS controller that gathers information in real-time from EVs [e.g., battery size, state-of-charge (SOC), desired SOC, and charge acceptance curve], grid (e.g., electricity price, allowed feeder capacity, ramp rate limit, and reactive power), and DERs (e.g., prediction for solar generation for PV systems). It solves a control optimization problem in real-time to find optimal setpoint for ESSs power dispatch, EVs charging rate, and grid inverters. The objectives are to (1) minimize the charging cost considering grid energy, demand charges, and battery energy, (2) minimize charging time to meet fast charging criterion, (3) keep high energy level on ESSs at the end of an operating period, while satisfying constraints related to grid, EVs, and power converters. b) Real-Time Energy Management System (RT-EMS) is a rule-based algorithm that has faster response than EMO. It receives optimal setpoint from EMO and actual measurements from the system and modify the setpoint to compensate for any fast disturbance in the system, until a new optimum solution is received. Fast disturbances may include vehicle connect/disconnect, unpredicted variation in DERs profiles, variation in grid voltage, errors in PV generation prediction, and others. In addition, RT-EMS regulates voltage at point of common coupling (PCC) by managing reactive power of grid converters.

Mohamed, Ahmed↗
DOE OSTI2024

Long-term Multimodal Recording Reveals Epigenetic Adaptation Routes in Dormant Breast Cancer Cells

Patients with estrogen receptor–positive breast cancer receive adjuvant endocrine therapies (ET) that delay relapse by targeting clinically undetectable micrometastatic deposits. Yet, up to 50% of patients relapse even decades after surgery through unknown mechanisms likely involving dormancy. To investigate genetic and transcriptional changes underlying tumor awakening, we analyzed late relapse patients and longitudinally profiled a rare cohort treated with long-term neoadjuvant ETs until progression. Next, we developed an in vitro evolutionary study to record the adaptive strategies of individual lineages in unperturbed parallel experiments. Our data demonstrate that ETs induce nongenetic cell state transitions into dormancy in a stochastic subset of cells via epigenetic reprogramming. Single lineages with divergent phenotypes awaken unpredictably in the absence of recurrent genetic alterations. Targeting the dormant epigenome shows promising activity against adapting cancer cells. Overall, this study uncovers the contribution of epigenetic adaptation to the evolution of resistance to ETs.

60 APPLIED LIFE SCIENCES↗
DOE OSTI2023

How Time Inefficient and Uncertain are Paratransit Trips Compared to Car Trips

The Americans with Disabilities Act (ADA) stipulates that paratransit mobility be comparable to public transit. However, with just under 5% of the population relying on public transportation, transit is not a representative benchmark. To highlight this inequality, we compare trip times by paratransit to counterfactual car-based travel. Using 2.5 years of demand data from the Denver Regional Transportation District's Access-a-Ride service, we compare paratransit trip times to counterfactual car-based trips for the same origin-destination pairs, controlling for various trip characteristics. Compared to car travel, the findings indicate high variability and uncertainty associated with paratransit trip times. For the same origin-destination pairs, the mean paratransit trip time is almost twice that of the mean car travel time, with a standard deviation for paratransit trip time fourfold that of the standard deviation for car trip time. For perspective, traveling an average of 10 mi during the 7-8 a.m. morning peak can take about 16 min by car with almost no variability, while that same trip can take an average of 25 min by paratransit, with 5% of trips being outside the 95% confidence interval and thus unpredictable. Paratransit trip time inefficiency tends to be particularly worse for females; older adults; those making trips between 9 and 11 a.m.; cash-paying customers; those making shorter trips; and those traveling during inclement weather, including cold temperatures. These findings suggest a need to re-assess using public transit as a benchmark for paratransit supply as regulated by the ADA.

accessible transportation and mobility↗
DOE OSTI2025

Non-circular electron beam spot welds in stainless steel alloys

Circularly symmetric-shaped spot welds are desirable for welding applications as they relate to heat and fluid flow conditions in the melt pool with predictable weld penetrations and repeatable results. Non-circular spot welds on the other hand result in undesirable and unpredictable weld penetrations or non-bridging of the liquid melt pool across the joint. Two known causes for non-circular melt pools occur when welding dissimilar metals, or when welding with skewed electron or laser beams that are not perpendicular to the surface. A largely unexplored additional factor, shown here, is an asymmetric power density distribution within the beam that can create non-circular melt pools even though the beam dimensions are much smaller than the melt pool itself.

36 MATERIALS SCIENCE↗
DOE OSTI2022

Planning decentralized urban renewable energy systems using algal cultivation for closed-loop and resilient communities

To tackle climate challenges, communities need to harvest renewable energy and resources on site locally to close the loops for enhancing the resilience of communities facing unpredictable and uncertain future changes. A decentralization planning of urban renewable energy systems is proposed by treating urban waste streams and producing biomass through applying algal biotechnology. When applying algal technology as a renewable and decentralized energy source in urban systems, the overall performance can vary by levels of urban nutrients, solar and CO 2 resources, and the transportation cost when considering its application to different urban densities, urban form, and the spatial scale of urban settings. This research explores three potential impacts on the algal system’s energy performance: (1) urban density, (2) urban form in different contexts, and (3) spatial scale. The research examines the impacts by testing urban settings given in actual contexts in Atlanta, Georgia, USA. Four neighborhoods representing the high-density urban, mid-density urban, mixed suburban, and typical suburban areas are investigated. The density-scale–performance relationships are explored through testing different urban forms of neighborhoods in both hypothetical and actual neighborhood settings. A GIS-based model is developed to estimate the overall energy performance of the decentralized renewable energy system in urban environments. Results show that the energy performance is positive mainly for high-density urban neighborhoods with small-to-medium scales, up to 0.36 MJ per ton of municipal solid wastes for actual settings and 0.37 MJ for hypothetical cases. Neighborhoods with higher density have higher energy performance while up scaling has negative effects on the energy performance with a low degree of significance. Optimal scales are found as a 1-km radius in real test beds and 1.3 km in hypothetical settings, in which the results show trade-offs between scaling effects in the system efficiency gain and the transportation cost increase.

Quan, Steven Jige↗