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At least 1,459 records · Page 81
All sourcesNASA NTRSDOE OSTI
DOE OSTI2021

Forest stand and canopy development unaltered by 12 years of CO2 enrichment*

Abstract Canopy structure—the size and distribution of tree crowns and the spatial and temporal distribution of leaves within them—exerts dominant control over primary productivity, transpiration and energy exchange. Stand structure—the spatial arrangement of trees in the forest (height, basal area and spacing)—has a strong influence on forest growth, allocation and resource use. Forest response to elevated atmospheric CO2 is likely to be dependent on the canopy and stand structure. Here, we investigated elevated CO2 effects on the forest structure of a Liquidambar styraciflua L. stand in a free-air CO2 enrichment experiment, considering leaves, tree crowns, forest canopy and stand structure. During the 12-year experiment, the trees increased in height by 5 m and basal area increased by 37%. Basal area distribution among trees shifted from a relatively narrow distribution to a much broader one, but there was little evidence of a CO2 effect on height growth or basal area distribution. The differentiation into crown classes over time led to an increase in the number of unproductive intermediate and suppressed trees and to a greater concentration of stand basal area in the largest trees. A whole-tree harvest at the end of the experiment permitted detailed analysis of canopy structure. There was little effect of CO2 enrichment on the relative leaf area distribution within tree crowns and there was little change from 1998 to 2009. Leaf characteristics (leaf mass per unit area and nitrogen content) varied with crown depth; any effects of elevated CO2 were much smaller than the variation within the crown and were consistent throughout the crown. In this young, even-aged, monoculture plantation forest, there was little evidence that elevated CO2 accelerated tree and stand development, and there were remarkably small changes in canopy structure. Questions remain as to whether a more diverse, mixed species forest would respond similarly.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2020

Verification of diesel spray ignition phenomenon in dual-fuel diesel-piloted premixed natural gas engine

Dual-fuel (DF) engines, in which premixed natural gas and air in an open-type combustion chamber is ignited by diesel-fuel pilot sprays, have been more popular for marine use than pre-chamber spark ignition (PCSI) engines because of their superior durability. However, control of ignition and combustion in DF engines is more difficult than in PCSI engines. In this context, here we focus on the ignition stability of n-heptane pilot-fuel jets injected into a compressed premixed charge of natural gas and air at low-load conditions. To aid understanding of the experimental data, chemical-kinetics simulations were carried out in a simplified engine-environment that provided insight into the chemical effects of methane (CH4) on pilot-fuel ignition. The simulations reveal that CH4 has an effect on both stages of n-heptane autoignition: the small, first-stage, cool-flame-type, low-temperature ignition (LTI) and the larger, second-stage, high-temperature ignition (HTI). As the ratio of pilot-fuel to CH4 entrained into the spray decreases, the initial oxidization of CH4 consumes the OH radicals produced by pilot-fuel decomposition during LTI, thereby inhibiting its progression to HTI. Using imaging diagnostics, the spatial and temporal progression of LTI and HTI in DF combustion are measured in a heavy-duty optical engine, and the imaging data are analyzed to understand the cause of severe fluctuations in ignition timing and combustion completeness at low-load conditions. Images of cool-flame and hydroxyl radical (OH*) chemiluminescence serve as indicators of LTI and HTI, respectively. The cycle-to-cycle and spatial variation in ignition extracted from the imaging data are used as key metrics of comparison. The imaging data indicate that the local concentration of the pilot-fuel and the richness of the surrounding natural-gas air mixture are important for LTI and HTI, but in different ways. In particular, higher injection pressures and shorter injection durations increase the mixing rate, leading to lower concentrations of pilot-fuel more quickly, which can inhibit HTI even as LTI remains relatively robust. Decreasing the injection pressure from 80 MPa to 40 MPa and increasing the injection duration from 500 µs to 760 µs maintained constant pilot-fuel mass, while promoting robust transition from LTI to HTI by effectively slowing the mixing rate. This allows enough residence time for the OH radicals, produced by the two-stage ignition chemistry of the pilot-fuel, to accelerate the transition from LTI to HTI before being consumed by CH4 oxidation. Thus from a practical perspective, for a premixed natural gas fuel–air equivalence-ratio, it is possible to improve the “stability” of the combustion process by solely manipulating the pilot-fuel injection parameters while maintaining constant mass of injected pilot-fuel. This allows for tailoring mixing trajectories to offset changes in fuel ignition chemistry, so as to promote a robust transition from LTI to HTI by changing the balance between the local concentration of the pilot-fuel and richness of the premixed natural gas and air. This could prove to be a valuable tool for combustion design to improve fuel efficiency or reduce noise or perhaps even reduce heat-transfer losses by locating early combustion away from in-cylinder walls.

42 ENGINEERING↗
DOE OSTI2024

In Situ Study on Fracture Behavior of Thick-Section Friction Stir-Welded AA 5083 Alloy

Friction stir welding (FSW) produces a gradient microstructure with distinct metallurgical zones. Here, the present study focuses on characterizing the fracture behavior during uniaxial loading across thick-section FSW joint in nonheat-treatable 5083 aluminum alloy. The hardness variation is linked to microstructural features across the weld zones through correlative microscopy. Notably, the heat-affected zone (HAZ) exhibits a lower hardness of 75 HV, while the thermomechanically affected zone (TMAZ) and stir zones (SZ) display a hardness of around 79HV. A marginal difference in hardness in HAZ prompts strain localization in HAZ on the advancing side of the weld, resulting in offset in fracture from the SZ, which is captured through in situ monitoring of the tensile test. Further, the postdeformation analysis reveals crack propagation along the maximum shear stress plane due to the coalescence of microvoids resulting from the fracturing and debonding of second-phase particles. Overall, this study provides valuable insight for optimizing the FSW process of AA 5083 alloy for thick-section applications.

36 MATERIALS SCIENCE↗
DOE OSTI2021

Ab initio molecular dynamics on quantum computers

Ab initio molecular dynamics (AIMD) is a valuable technique for studying molecules and materials at finite temperatures where the nuclei evolve on potential energy surfaces obtained from accurate electronic structure calculations. In this work, we present an approach to running AIMD simulations on noisy intermediate-scale quantum (NISQ)-era quantum computers. The electronic energies are calculated on a quantum computer using the variational quantum eigensolver (VQE) method. Algorithms for computation of analytical gradients entirely on a quantum computer require quantum fault-tolerant hardware, which is beyond NISQ-era. Therefore, we compute the energy gradients numerically using finite differences, the Hellmann-Feynman theorem, and a correlated sampling technique. This method only requires additional classical calculations of electron integrals for each degree of freedom without any additional computations on a quantum computer beyond the initial VQE run. As a proof of concept, AIMD simulations are demonstrated for the H-2 molecule on IBM quantum devices. In addition, we demonstrate the validity of the method for larger molecules using full configuration interaction wave functions. As quantum hardware and noise mitigation techniques continue to improve, the method can be utilized for studying larger molecular systems.

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

Grassland productivity responds unexpectedly to dynamic light and soil water environments induced by photovoltaic arrays

Abstract Agrivoltaic (AV) systems are designed to coproduce photovoltaic (PV) energy on lands simultaneously supporting agriculture (food/forage production). PV infrastructure in agroecosystems alters resources critical for plant growth, and water‐limited agroecosystems such as grasslands are likely to be particularly sensitive to the unique spatial and temporal patterns of incident sunlight and soil water inherent within AV systems. However, the impact of resource alteration on forage production, the primary ecosystem service from managed grasslands, is poorly resolved. Here, we evaluated seasonal patterns of soil moisture (SM) and diurnal variation in incident sunlight (photosynthetic photon flux density [PPFD]) in a single‐axis‐tracking AV system established in a formerly managed semiarid C 3 grassland in Colorado. Our goals were to (1) quantify dynamic patterns of PPFD and SM within a 1.2 MW PV array in a perennial grassland, and (2) determine how aboveground net primary production (ANPP) and photosynthetic parameters responded to the resource patterns created by the PV array. We hypothesized that spatial variability in ANPP would be strongly related to SM patterns, typical of most grasslands. We measured significant reductions in ANPP directly beneath PV panels, where SM and PPFD were both low. However, in locations with significantly increased SM from the shedding and redistribution of precipitation by PV panels, ANPP was not increased. Instead, ANPP was greatest in locations where plants were shaded in the afternoon but received high levels of PPFD in the morning hours, when air temperatures and vapor pressure deficits were relatively low. Thus, contrary to expectations, we found relatively weak relationships between SM and ANPP despite significant spatial variability in both. Further, there was little evidence that light‐saturated photosynthesis ( A sat ) and quantum yield of CO 2 assimilation (ϕCO 2 ) differed for plants growing directly beneath (lowest PPFD) versus between (highest PPFD) PV panels. Overall, the AV system established in this semiarid managed grassland did not alter patterns of ANPP in ways predictable from past studies of controls of ANPP in open grasslands. However, our results suggest that the diurnal timing of low versus high periods of PPFD incident on plants is an important determinant of productivity patterns in grasslands.

14 SOLAR ENERGY↗
DOE OSTI2024

Correlated Anion Disorder in Heteroanionic Cubic TiOF 2

Resolving anion configurations in heteroanionic materials is crucial for understanding and controlling their properties. For anion-disordered oxyfluorides, conventional Bragg diffraction cannot fully resolve the anionic structure, necessitating alternative structure determination methods. We have investigated the anionic structure of anion-disordered cubic (ReO 3 -type) TiOF 2 using X-ray pair distribution function (PDF), 19 F MAS NMR analysis, density functional theory (DFT), cluster expansion modeling, and genetic-algorithm structure prediction. Our computational data predict short-range anion ordering in TiOF 2 , characterized by predominant cis-[O 2 F 4 ] titanium coordination, resulting in correlated anion disorder at longer ranges. To validate our predictions, we generated partially disordered supercells using genetic-algorithm structure prediction and computed simulated X-ray PDF data and 19 F MAS NMR spectra, which we compared directly to experimental data. To construct our simulated 19 F NMR spectra, we derived new transformation functions for mapping calculated magnetic shieldings to predicted magnetic chemical shifts in titanium (oxy)fluorides, obtained by fitting DFT-calculated magnetic shieldings to previously published experimental chemical shift data for TiF 4 . We find good agreement between our simulated and experimental data, which supports our computationally predicted structural model and demonstrates the effectiveness of complementary experimental and computational techniques in resolving anionic structure in anion-disordered oxyfluorides. From additional DFT calculations, we predict that increasing anion disorder makes lithium intercalation more favorable by, on average, up to 2 eV, highlighting the significant effect of variations in short-range order on the intercalation properties of anion-disordered materials.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2020

Tailoring a Global Iron Regulon to a Uropathogen

Pathogenicity islands and plasmids bear genes for pathogenesis of various Escherichia coli pathotypes. Although there is a basic understanding of the contribution of these virulence factors to disease, less is known about variation in regulatory networks in determining disease phenotypes. Here, we dissected a regulatory network directed by the conserved iron homeostasis regulator, ferric uptake regulator (Fur), in uropathogenic E. coli (UPEC) strain CFT073. Comparing anaerobic genome-scale Fur DNA binding with Fur-dependent transcript expression and protein levels of the uropathogen to that of commensal E. coli K-12 strain MG1655 showed that the Fur regulon of the core genome is conserved but also includes genes within the pathogenicity/genetic islands. Unexpectedly, regulons indicative of amino acid limitation and the general stress response were also indirectly activated in the uropathogen fur mutant, suggesting that induction of the Fur regulon increases amino acid demand. Using RpoS levels as a proxy, addition of amino acids mitigated the stress. In addition, iron chelation increased RpoS to the same levels as in the fur mutant. The increased amino acid demand of the fur mutant or iron chelated cells was exacerbated by aerobic conditions, which could be partly explained by the O 2 -dependent synthesis of the siderophore aerobactin, encoded by an operon within a pathogenicity island. Taken together, these data suggest that in the iron-poor environment of the urinary tract, amino acid availability could play a role in the proliferation of this uropathogen, particularly if there is sufficient O 2 to produce aerobactin. IMPORTANCE Host iron restriction is a common mechanism for limiting the growth of pathogens. We compared the regulatory network controlled by Fur in uropathogenic E. coli (UPEC) to that of nonpathogenic E. coli K-12 to uncover strategies that pathogenic bacteria use to overcome iron limitation. Although iron homeostasis functions were regulated by Fur in the uropathogen as expected, a surprising finding was the activation of the stringent and general stress responses in the uropathogen fur mutant, which was rescued by amino acid addition. This coordinated global response could be important in controlling growth and survival under nutrient-limiting conditions and during transitions from the nutrient-rich environment of the lower gastrointestinal (GI) tract to the more restrictive environment of the urinary tract. The coupling of the response of iron limitation to increased demand for amino acids could be a critical attribute that sets UPEC apart from other E. coli pathotypes.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2022

Octane Requirements of Lean Mixed-Mode Combustion in a Direct-Injection Spark-Ignition Engine

Here, this study investigates the octane requirements of a hybrid flame propagation and controlled autoignition mode referred to as mixed-mode combustion (MMC), which allows for strong control over combustion parameters via a spark-initiated deflagration phase. Due to the throughput limitations associated with both experiments and 3-D computational fluid dynamics calculations, a hybrid 0-D and 1-D modeling methodology was developed, supported by experimental validation data. This modeling approach relied on 1-D, two-zone engine simulations to predict bulk in-cylinder thermodynamic conditions over a range of engine speeds, compression ratios, intake pressures, trapped residual levels, fueling rates, and spark timings. Those predictions were then transferred to a 0-D chemical kinetic model, which was used to evaluate the autoignition behavior of fuels when subjected to temperature–pressure trajectories of interest. Finally, the predicted autoignition phasings were screened relative to the progress of the modeled deflagration-based combustion in order to determine if an operating condition was feasible or infeasible due to knock or stability limits. The combined modeling and experimental results reveal that MMC has an octane requirement similar to modern stoichiometric spark-ignition engines in that fuels with high research octane number (RON) and high octane sensitivity (S) enable higher loads. Experimental trends with varying RON and S were well predicted by the model for 1000 and 1400 rpm, confirming its utility in identifying the compatibility of a fuel’s autoignition behavior with an engine configuration and operating strategy. However, the model was not effective in predicting (nor designed to predict) operability limits due to cycle-to-cycle variations, which experimentally inhibited operation of some fuels at 2000 rpm. Putting the operable limits and efficiency from MMC in the context of a state-of-the-art engine, the MMC showed superior efficiencies over the range investigated, demonstrating the potential to further improve fuel economy.

33 ADVANCED PROPULSION SYSTEMS↗
DOE OSTI2021

CO 2 Hydrogenation on ZrO 2 /Cu(111) Surfaces: Production of Methane and Methanol

The conversion and utilization of carbon dioxide is a critical challenge for the control of greenhouse gas pollution and in the production of high value chemicals in C1 chemistry. ZrO 2 /Cu(111) is an inverse oxide/metal catalyst that displays high activity and stability for the hydrogenation of CO 2 into methanol at 500-600 K. At elevated temperatures, ZrO 2 grows on a CuO x /Cu(111) substrate forming islands of 10-12 nm in size and an average height of ~ 3 Å. Reaction with H 2 leads to the removal of the copper oxide producing ZrO 2 /Cu(111) surfaces which are very active for the binding and dissociation of CO 2 into CO and C. After exposing ZrO 2 /Cu(111) to moderate or elevated pressures of a CO 2 /H 2 mixture at 300 K, atomic C and minor amounts of CH x O and CO x are deposited on the catalyst surface. The adsorbed CH x O and CO x disappear upon heating above 400 K. The catalytic tests for CO 2 hydrogenation give CO as the main reaction product and CH 4 and CH 3 OH as secondary products. The relative yields of methane and methanol change with time and track the amount of atomic C deposited on the active ZrO 2 /Cu(111) surface. The formation of methane stops once the catalyst surface is saturated with C. Under steady-state conditions, ZrO 2 /Cu(111) is a much better catalyst for methanol synthesis than ZnO/Cu(111). This trend reflects variations in the size of the oxide islands and in the strength of oxide-metal interactions. The use of an inverse oxide/metal configuration is an important synthetic tool when preparing active, selective, and stable catalysts for CO 2 hydrogenation.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2021

Rapid estimation of photosynthetic leaf traits of tropical plants in diverse environmental conditions using reflectance spectroscopy

Tropical forests are one of the main carbon sinks on Earth, but the magnitude of CO 2 absorbed by tropical vegetation remains uncertain. Terrestrial biosphere models (TBMs) are commonly used to estimate the CO 2 absorbed by forests, but their performance is highly sensitive to the parameterization of processes that control leaf-level CO 2 exchange. Direct measurements of leaf respiratory and photosynthetic traits that determine vegetation CO 2 fluxes are critical, but traditional approaches are time-consuming. Reflectance spectroscopy can be a viable alternative for the estimation of these traits and, because data collection is markedly quicker than traditional gas exchange, the approach can enable the rapid assembly of large datasets. However, the application of spectroscopy to estimate photosynthetic traits across a wide range of tropical species, leaf ages and light environments has not been extensively studied. Here, we used leaf reflectance spectroscopy together with partial least-squares regression (PLSR) modeling to estimate leaf respiration ( R dark25 ), the maximum rate of carboxylation by the enzyme Rubisco ( V cmax25 ), the maximum rate of electron transport ( J max25 ), and the triose phosphate utilization rate ( T p25 ), all normalized to 25°C. We collected data from three tropical forest sites and included leaves from fifty-three species sampled at different leaf phenological stages and different leaf light environments. Our resulting spectra-trait models validated on randomly sampled data showed good predictive performance for V cmax25 , J max25 , T p25 and R dark25 (RMSE of 13, 20, 1.5 and 0.3 μmol m -2 s -1 , and R 2 of 0.74, 0.73, 0.64 and 0.58, respectively). The models showed similar performance when applied to leaves of species not included in the training dataset, illustrating that the approach is robust for capturing the main axes of trait variation in tropical species. We discuss the utility of the spectra-trait and traditional gas exchange approaches for enhancing tropical plant trait studies and improving the parameterization of TBMs.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2025

Biophysical model of eelgrass and water quality in Coos Bay, OR shows greater mitigation potential for ocean acidification than hypoxia

Seagrass beds provide important ecosystem services and are valued, in part, for their potential to mediate stressors such as ocean acidification and hypoxia (OAH) for sensitive species. However, the susceptibility of seagrasses to anthropogenic impacts and recent declines motivate the need to better understand the drivers of seagrass and the water quality consequences that occur with variation in seagrass abundance. To meet this need, we leveraged existing monitoring data (water quality and seagrass), hydrodynamic circulation model, and biogeochemical model framework with seagrass submodel, to produce a biophysical model of Coos Bay estuary, Oregon, U.S. The model includes biogeochemical processes involving water quality, plankton, seagrass, and sediment-water interactions. Ecosystem models like this are useful for evaluating complex estuarine systems because they allow us to extend our understanding of system dynamics beyond existing observations and perform experiments to identify the processes driving observed patterns. We used the biophysical model of Coos Bay to evaluate the dynamics of water quality and native eelgrass (Zostera marina) under three eelgrass abundance scenarios (zero eelgrass, current extent, and maximum observed extent) to elucidate the relationship between eelgrass and OAH. Including eelgrass in the Coos Bay model produced results that more closely resembled water quality observations - dissolved oxygen (DO) and pH were more dynamic in simulations with eelgrass, often having both higher highs and lower lows. While there were some areas of the estuary where DO improved with the addition of eelgrass to the model there was overall a small net increase in harmful DO conditions (based on a salmon physiological threshold). In contrast, ocean acidification conditions, pH and calcium carbonate saturation state for aragonite (Ω), were improved (based on oyster requirements) with the addition of eelgrass - although the magnitude of improvement differed seasonally and spatially. Our new model represents a useful tool - one which accounts for and controls the relevant physical and biogeochemical processes - to evaluate conditions that confer resilience or enhance vulnerability to OAH in an important Pacific Northwest coastal estuary and results can inform the OAH-related dynamics occurring in other eastern boundary current estuaries.

FVCOM-ICM↗
DOE OSTI2024

Autoregressive distributed lag-based dynamic uniformity modeling and monitoring approaches for superconductor manufacturing

High-temperature superconductors (HTS), known for their high efficiency and low energy loss, have found profound applications across various fields, driving the demand for long, uniformly performing tapes. However, ensuring uniform performance over extended lengths of HTS tapes, often characterized by the consistency of critical current, remains challenging due to fluctuations in growth conditions during manufacturing. Here, to elucidate the mechanisms underlying variations in tape uniformity and enable real-time monitoring of associated parameters, we propose an Autoregressive Distributed Lag (ADL)-based Dynamic Uniformity Modeling and Monitoring (ADUM2) approach. This method integrates uniformity measurement, the identification of critical process parameters and real-time monitoring within the manufacturing process. The ADUM2 approach is applied to the advanced metal organic chemical vapor deposition (A-MOCVD) process, a pilot-scale method for superconductor manufacturing. Our model demonstrates superior performance compared to benchmark methods, accounting for over 80% of the total variance in the data and identifying 13 key process parameters influencing the uniformity of HTS tapes. This study offers significant insights into the high-temperature superconductor manufacturing process and holds the potential to facilitate the production of cost-effective, uniformly performing long superconducting tapes in the future.

autoregressive distributed lag analysis↗
DOE OSTI2023

Genetic control of photoprotection and photosystem II operating efficiency in plants

Summary Photoprotection against excess light via nonphotochemical quenching (NPQ) is indispensable for plant survival. However, slow NPQ relaxation under low light conditions can decrease yield of field‐grown crops up to 40%. Using semi‐high‐throughput assay, we quantified the kinetics of NPQ and photosystem II operating efficiency (ΦPSII) in a replicated field trial of more than 700 maize ( Zea mays ) genotypes across 2 yr. Parametrized kinetics data were used to conduct genome‐wide association studies. For six candidate genes involved in NPQ and ΦPSII kinetics in maize the loss of function alleles of orthologous genes in Arabidopsis ( Arabidopsis thaliana ) were characterized: two thioredoxin genes, and genes encoding a transporter in the chloroplast envelope, an initiator of chloroplast movement, a putative regulator of cell elongation and stomatal patterning, and a protein involved in plant energy homeostasis. Since maize and Arabidopsis are distantly related, we propose that genes involved in photoprotection and PSII function are conserved across vascular plants. The genes and naturally occurring functional alleles identified here considerably expand the toolbox to achieving a sustainable increase in crop productivity.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2025

Lie-algebraic classical simulations for quantum computing

The classical simulation of quantum dynamics plays an important role in our understanding of quantum complexity and in the development of quantum technologies. Efficient techniques such as those based on the Gottesman-Knill theorem for Clifford circuits, tensor networks for low entanglement-generating circuits, or Wick's theorem for fermionic Gaussian states have become central tools in quantum computing. In this work, we contribute to this body of knowledge by presenting a framework for classical simulations, dubbed “𝔤-sim”, which is based on the underlying Lie algebraic structure of the dynamical process. When the dimension of the algebra grows at most polynomially in the system size, there exist observables for which the simulation is efficient. Indeed, we show that 𝔤-sim enables new regimes for classical simulations, is able to deal with certain forms of noise in the evolution, as well as can be used to tackle several paradigmatic variational and nonvariational quantum computing tasks. For the former, we perform Lie-algebraic simulations to train and optimize parametrized quantum circuits (thus effectively showing that some variational models can be dequantized), design enhanced parameter initialization strategies, solve tasks of quantum circuit synthesis, and train a quantum-phase classifier. For the latter, we report large-scale noiseless and noisy simulations on benchmark problems. By comparing the limitations of 𝔤-sim and certain Wick's theorem-based simulations, we find that the two methods become inefficient for different types of states or observables, hinting at the existence of distinct, nonequivalent resources for classical simulation.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2025

Realistic Noise Generation to Enhance Realism of Virtual Lidar Scans

Many real-world phenomena corrupt light detection and ranging (lidar) measurements, such as laser energy attenuation, variations in aerosol concentration and composition with height, and hard target returns. Accurate studies of lidar scans using virtual lidar methods should include some realistic model of these corrupting effects to generate more realistic simulations of lidar scans. We present a simple model that characterizes noise caused by energy attenuation and aerosol stratification. The model requires limited inputs and is developed for a Halo Photonics Streamline XR lidar but is readily generalizable for other lidar systems. A critical component of this model is a model of the standard deviation of measured wind speed as a function of the backscattered signal’s signal-to-noise ratio. We derive a general model for this behavior that can be adapted to different scan settings.

17 WIND ENERGY↗
DOE OSTI2025

Monitoring strain evolution in water-sand systems using distributed acoustic sensing for geohazard early warning

Rainfall-driven hazards such as landslides, debris flows, and earthen dam failures often arise when water changes the internal strain within sand. This study evaluates the ability of distributed acoustic sensing to monitor these strain changes in real time. We embed a fiber-optic cable in a sand-filled glass cylinder and run controlled dry- and wet-sand experiments to measure how strain develops as water infiltrates, saturates, and drains from the sand. The sensing system detects uneven water movement in dry sand and enables millimeter-scale estimates of infiltration rates, and in wet sand it tracks rising water levels, delayed strain peaks after saturation, and abrupt strain shifts during drainage. These results show that fiber-optic sensing captures subtle strain evolution throughout the full water-sand interaction cycle. The study demonstrates that fiber-optic sensing offers promising potential for real-time and cost-effective monitoring and early warning of rainfall-induced geohazards.

58 GEOSCIENCES↗
DOE OSTI2026

Latent heat thermal energy storage performance maps enabling fast & accurate building energy simulations

Thermal energy storage (TES) using phase change materials (PCMs) has gained attention as an effective approach to manage energy demand fluctuations and shift peak building loads. PCM embedded heat exchangers (PCM-HXs) offer high energy storage density and low temperature variation during phase change, being suitable for load-shifting applications. However, this component is typically evaluated using computationally expensive methods, which present significant challenges when the ultimate goal is to assess the performance of PCM-HX integrated thermal energy storage systems in the full building context. In this paper, we present a methodology to generate highly accurate and computationally efficient PCM-HX performance maps which can be easily integrated into building energy simulation tools to analyze the feasibility of space conditioning systems with latent heat PCM-based TES. The performance maps are generated using a computationally efficient PCM-HX simulation tool based on a Generalized Resistance-Capacitance Model (GRCM) which can simulate arbitrary PCM-HXs with high accuracy and significantly less computational effort compared to full CFD simulations. The methodology was verified for a case study considering a 5-ton (~17.5 kW) air-to-water heat pump-thermal energy storage system (HP-TES), which was co-simulated in Modelica for a DOE prototype small-office building in Vienna, Austria, using Spawn of EnergyPlus™. The TES performance maps provided accurate predictions of PCM-HX behavior when used as Modelica component, with deviations within 2-4% while also achieving at least 103 computational time reduction. Leveraging this faster prediction capability, four PCMs with different melting temperatures for cooling (12°C, 16°C) and heating (31°C, 36°C) were assessed to investigate their impact on system performance. This work highlights the importance of robust PCM-HX models for efficient and high-fidelity building-level simulations, presenting new opportunities for advanced control strategy development and parametric analysis of TES configurations in a computationally efficient manner

Modelica Building Simulations↗