Search NASA⌕ Search

SEARCH · Search NASA

Results for “Generations”

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.

Quote a phrase for an exact phrase match. Source license links do not imply unrestricted reuse.

At least 487 records · Page 27
All sourcesNASA NTRSDOE OSTI
DOE OSTI2019

3D printed droplet generation devices for serial femtosecond crystallography enabled by surface coating

The role of surface wetting properties and their impact on the performance of 3D printed microfluidic droplet generation devices for serial femtosecond crystallography (SFX) are reported herein. SFX is a novel crystallography method enabling structure determination of proteins at room temperature with atomic resolution using X-ray free-electron lasers (XFELs). In SFX, protein crystals in their mother liquor are delivered and intersected with a pulsed X-ray beam using a liquid jet injector. Owing to the pulsed nature of the X-ray beam, liquid jets tend to waste the vast majority of injected crystals, which this work aims to overcome with the delivery of aqueous protein crystal suspension droplets segmented by an oil phase. For this purpose, 3D printed droplet generators that can be easily customized for a variety of XFEL measurements have been developed. The surface properties, in particular the wetting properties of the resist materials compatible with the employed two-photon printing technology, have so far not been characterized extensively, but are crucial for stable droplet generation. This work investigates experimentally the effectiveness and the long-term stability of three different surface treatments on photoresist films and glass as models for our 3D printed droplet generator and the fused silica capillaries employed in the other fluidic components of an SFX experiment. Finally, the droplet generation performance of an assembly consisting of the 3D printed device and fused silica capillaries is examined. Stable and reproducible droplet generation was achieved with a fluorinated surface coating which also allowed for robust downstream droplet delivery. Experimental XFEL diffraction data of crystals formed from the large membrane protein complex photosystem I demonstrate the full compatibility of the new injection method with very fragile membrane protein crystals and show that successful droplet generation of crystal-laden aqueous droplets intersected by an oil phase correlates with increased crystal hit rates.

47 OTHER INSTRUMENTATION↗
DOE OSTI2023

Net Load Forecasting With Disaggregated Behind-the-Meter PV Generation

As worldwide use of residential photovoltaic (PV) systems grows, system operators and utilities will need to transition from forecasting pure demand to forecasting net load with behind-the-meter (BTM) PV generation. However, PV generation can be difficult to predict and the measurements of PV generation from BTM residential systems are often invisible behind a measurement of the net load, making net load forecasting challenging. This paper proposes a novel two-stage framework for net load forecasting in areas with limited observability and high BTM PV generation. First, the profiles of observable customers are used to disaggregate the net load measurements into the pure load and PV generation. Then, separate models are used to forecast the PV generation and pure load individually, and the results are combined for a net load forecast. Further, this paper also proposes a compensator for correcting the error of the net load forecast, using historical forecast errors of the PV generation, pure load, and net load. The proposed framework is tested through two case studies for areas with high BTM PV penetration and less than 10% observable customers. The two-stage forecasting model is compared to two benchmark methods - a time series forecasting model, and a model that forecasts the net load directly using historical net load measurements. Results show that the proposed disaggregation-forecasting framework reduces the error of the net load forecast compared to both benchmark models. In addition, when the net load forecast error is periodic, the compensator can correct the error to improve the forecast accuracy.

14 SOLAR ENERGY↗
DOE OSTI2020

Diesel Generator Model Parameterization for Microgrid Simulation Using Hybrid Box-Constrained Levenberg-Marquardt Algorithm

Existing generator parameterization methods, typically developed for large turbine generator units, are difficult to apply to small kW-level diesel generators in microgrid applications. Here, this article presents a model parameterization method that estimates a complete set of kW-level diesel generator parameters simultaneously using only load-step-change tests with limited measurement points. This method provides a more cost-efficient and robust approach to achieve high-fidelity modeling of diesel generators for microgrid dynamic simulation. A two-stage hybrid box-constrained Levenberg-Marquardt (H-BCLM) algorithm is developed to search the optimal parameter set given the parameter bounds. A heuristic algorithm, namely Generalized Opposition-based Learning Genetic Algorithm (GOL-GA), is applied to identify proper initial estimates at the first stage, followed by a modified Levenberg-Marquardt algorithm designed to fine tune the solution based on the first-stage result. The proposed method is validated against dynamic simulation of a diesel generator model and field measurements from a 16kW diesel generator unit.

42 ENGINEERING↗
DOE OSTI2017

Survey of Neutron Generators for Active Interrogation

Some of these commercially available generators meet all of the requirements in Table 1, but there are other concerns. Most generators containing SF6 will be required to have the SF6 gas removed for shipping because of DOT regulations. However, Thermo Fisher has a DOT exemption. The P211 and B211 from Thermo Fisher meet the requirements listed in Table 1, but they are old designs and are no longer offered for sale. Also, they require 15 minutes or more of warmup before neutron output is available, and they lack a modern digital control. The nGen-300C from Starfire Industries is interesting because it is a portable system, but it uses the DD reaction for 2.5 MeV neutrons, which are not as penetrating as the 14 MeV neutrons from the DT reaction. The MP 320 from Thermo Fisher is another portable system, but the minimum pulse rate is 250 Hz, which is too fast for measurement of delayed neutrons and re-interrogation by delayed neutrons between pulses. The Genie 16 from Sodern (from France) probably meets the requirements, but the required power is probably too high for battery operation. The generators from Russia and China may be difficult to purchase, and service may not be available. The power required by some of these generators is low enough that batteries can be used. The portable units, nGen-300C and the MP320, could easily be operated with batteries. Other generators with low power requirements, as specified in the above vendors list, could possibly be operated with reason size batteries. The batteries do not need to be internal to the generator, but can be in a separate package. The availability of high capacity lithium batteries with sophisticated safety circuits makes battery operation more possible now than when lead acid batteries were used. The best path forward probably requires working with vendors of the existing systems. If Starfire Industries could be persuaded to put tritium in their nGen-300C generator, possibly in collaboration with a national laboratory, this would provide the 14-MeV neutrons needed. Another possibility is a modification of the Thermo Fisher MP 320 to run at 50 to 100 Hz. More discussions with these vendors, and possibly others, are required to determine their interest and possible costs.

43 PARTICLE ACCELERATORS↗
DOE OSTI2019

Measurements of Hydrogen Generation Rates using a Sealed Reactor System - 19428

Sealed reactor tests were performed to measure the hydrogen generation rate (HGR) from stored radioactive waste at the Savannah River Site. HGR may be very low, on the order of 7.5 x 10{sup -13} (m{sup 3}/h)/L [that is, cubic meters of H{sub 2} generated per hour per liter of radioactive liquid waste, or 10{sup -10} (ft{sup 3}/h)/gal]. Because the estimated HGR limit of detection for an open, continuous flow, system is approximately 7.5 x 10{sup -10} (m{sup 3}/h)/L [or 10{sup -7} (ft{sup 3}/h)/gal], a more sensitive method was needed. By accumulating generated gasses in a sealed system without a continuous purge gas, the resulting concentrations can increase the sensitivity of measurement, which is based on time of heating. In 2017, Savannah River Remediation declared a Potential Inadequacy in the Safety Analysis related to the potential thermal decomposition of organics that generate hydrogen in each of three Liquid Waste facilities: Concentration, Storage and Transfer Facility, Saltstone Production Facility, and the Defense Waste Processing Facility. The research for this study concerns low activity waste of Tank 50, which feeds the Saltstone Production Facility. This study evaluated the impact of organics including formate on the generation of H{sub 2}. Samples of SRS Tank 50 waste, which is a nominal 5 molar sodium salt solution, were sealed in stainless steel reactors and held at varying temperatures, e.g., 50 deg. C, 75 deg. C, 100 deg. C, and 120 deg. C, to determine if organic compounds are decomposing into H2. The experiments included trace solids used to stabilize waste in grout, e.g., grout-premix and Blast Furnace Slag, to determine if any solid phase reactions are present, which would accelerate or inhibit the generation of H{sub 2} at these temperatures. This paper describes the sealed reactors designed and constructed at Savannah River National Laboratory and the radioactive tests that were performed to measure HGR in both oxic and anoxic atmospheres. The shakedown tests showed the sealed reactors to be leak tight and hydrogen concentrations from calibrated standards could be accurately measured. Previous simulant tests helped to perfect the test methods and better design the radioactive tests. The radioactive results showed that the rate of hydrogen generated from Tank 50 waste, over a range of temperatures from 30 deg. C up to 120 deg. C, is bounded by an empirical relation (Hu Equation) that can be used to approximate HGRs in Tank 50 radioactive waste. (authors)

12 MANAGEMENT OF RADIOACTIVE AND NON-RADIOACTIVE W↗
DOE OSTI2024

Cancer Incidence Trends in Successive Social Generations in the US

Importance: The incidence of some cancers in the US is increasing in younger age groups, but underlying trends in cancer patterns by birth year remain unclear. Objective: To estimate cancer incidence trends in successive social generations. Design, Setting, and Participants: In this cohort study, incident invasive cancers were ascertained from the Surveillance, Epidemiology, and End Results (SEER) program’s 13-registry database (November 2020 submission, accessed August 14, 2023). Invasive cancers diagnosed at ages 35 to 84 years during 1992 to 2018 within 152 strata were defined by cancer site, sex, and race and ethnicity. Exposure: Invasive cancer. Main Outcome and Measures: Stratum-specific semiparametric age-period-cohort (SAGE) models were fitted and incidence per 100 000 person-years at the reference age of 60 years was calculated for single-year birth cohorts from 1908 through 1983 (fitted cohort patterns [FCPs]). The FCPs and FCP incidence rate ratios (IRRs) were compared by site for Generation X (born between 1965 and 1980) and Baby Boomers (born between 1946 and 1964). Results: A total of 3.8 million individuals with invasive cancer (51.0% male; 8.6% Asian or Pacific Islander, 9.5% Hispanic, 10.4% non-Hispanic Black, and 71.5% non-Hispanic White) were included in the analysis. In Generation X vs Baby Boomers, FCP IRRs among women increased significantly for thyroid (2.76; 95% CI, 2.41-3.15), kidney (1.99; 95% CI, 1.70-2.32), rectal (1.84; 95% CI, 1.52-2.22), corpus uterine (1.75; 95% CI, 1.40-2.18), colon (1.56; 95% CI, 1.27-1.92), and pancreatic (1.39; 95% CI, 1.07-1.80) cancers; non-Hodgkins lymphoma (1.40; 95% CI, 1.08-1.82); and leukemia (1.27; 95% CI, 1.03-1.58). Among men, IRRs increased for thyroid (2.16; 95% CI, 1.87-2.50), kidney (2.14; 95% CI, 1.86-2.46), rectal (1.80; 95% CI, 1.52-2.12), colon (1.60; 95% CI, 1.32-1.94), and prostate (1.25; 95% CI, 1.03-1.52) cancers and leukemia (1.34; 95% CI, 1.08-1.66). Lung (IRR, 0.60; 95% CI, 0.50-0.72) and cervical (IRR, 0.71; 95% CI, 0.57-0.89) cancer incidence decreased among women, and lung (IRR, 0.51; 95% CI, 0.43-0.60), liver (IRR, 0.76; 95% CI, 0.63-0.91), and gallbladder (IRR, 0.85; 95% CI, 0.72-1.00) cancer and non-Hodgkins lymphoma (IRR, 0.75; 95% CI, 0.61-0.93) incidence decreased among men. For all cancers combined, FCPs were higher in Generation X than for Baby Boomers because gaining cancers numerically overtook falling cancers in all groups except Asian or Pacific Islander men. Conclusions and Relevance: In this model-based cohort analysis of incident invasive cancer in the general population, decreases in lung and cervical cancers in Generation X may be offset by gains at other sites. Generation X may be experiencing larger per-capita increases in the incidence of leading cancers than any prior generation born in 1908 through 1964. On current trajectories, cancer incidence could remain high for decades.

60 APPLIED LIFE SCIENCES↗
DOE OSTI2023

A Minkowski difference-based advancing front packing technique for generating convex noncircular particles in complex domains

In this work, a Minkowski difference-based advancing front approach is proposed to generate convex and non-circular particles in a predefined computational domain. Two specific algorithms are developed to handle the contact conformity of generated particles with the boundaries of the computational domain. The first, called the open form, is used to handle the smooth contact of generated particles with (external) boundaries, while the other, called the closed form, is proposed to handle the internal boundaries of a computational domain with a complex cavity. The Gilbert-Johnson-Keerthi (GJK) method is used to efficiently solve the contact detection between the newly generated particle at the front and existing particles. Furthermore, the problem of one-sided particle lifting, which can cause some defects in the packing structure in existing advancing front methods during packing generation, is highlighted and an effective solution is developed. Several examples of increasing complexity are used to demonstrate the efficiency and applicability of the proposed packing generation approach. The numerical results show that the generated packing is not only more uniform, but also achieves a higher packing density than existing advancing front methods.

42 ENGINEERING↗
DOE OSTI2024

Advanced multimaterial shape optimization methods as applied to advanced manufacturing of wind turbine generators

Abstract Currently, many utility‐scale wind turbine generator original equipment manufacturers are dependent on imported rare earth permanent magnets, which are susceptible to market risks from cost instability. To lower the production costs of these generators and stay competitive in the market, several small wind manufacturers are pursuing continuous improvements to both generator design and manufacturing. However, traditional design and manufacturing methods have yielded marginal improvements in wind power performance. This work presents novel methods to redesign a baseline 15‐kW wind turbine generator with reduced rare‐earth permanent magnets by leveraging cutting‐edge three‐dimensional (3D) printed polymer‐bonded permanent magnets and steel. Symmetric, asymmetric, and multimaterial‐magnet parametrization methods are introduced for shape optimization. We extend the symmetric and asymmetric methods to the back iron in the stator to further investigate the impact and opportunities for performance improvements with lesser active materials. We employ a design‐of‐experiments approach with parametric computer‐aided design for shape generation and evaluate different designs by magneto‐thermal modeling and finite‐element analysis. We use adaptive sampling technique to identify better performing designs with lesser magnet mass, higher efficiency, and lower cogging torque when compared with the baseline generator. Asymmetric pole designs resulted in a magnet mass in the range of 4.77–5.37 kg, which was 27%–35% lighter than the baseline generator, suggesting that a new design freedom exists that can be enabled by advanced manufacturing, such as 3D printing. Shaping the back iron in the stator resulted in material savings in electrical steel of up to 14.62 kg, which was 20% lighter than the baseline stator. We conducted a structural analysis to evaluate an optimized asymmetric rotor design from the point of view of mechanical integrity and air‐gap stiffness. The magnetically optimal shape profile was shown as having a positive impact on the radial stiffness, and an optimal solution was discovered to reduce the structural mass by nearly 30 kg, which was 29% lighter than the baseline.

17 WIND ENERGY↗
DOE OSTI2017

Regional water consumption for hydro and thermal electricity generation in the United States

Water is an essential resource for most electric power generation technologies. Thermal power plants typically require a large amount of cooling water whose evaporation is regarded to be consumed. Hydropower plants result in evaporative water loss from the large surface areas of the storing reservoirs. This paper estimated the regional water consumption factors (WCFs) for thermal and hydro electricity generation in the United States, because the WCFs of these power plants vary by region and water supply and demand balance are of concern in many regions. For hydropower, total WCFs were calculated using a reservoir’s surface area, state-level water evaporation, and background evapotranspiration. Then, for a multipurpose reservoir, a fraction of its WCF was allocated to hydropower generation based on the share of the economic valuation of hydroelectricity among benefits from all purposes of the reservoir. For thermal power plants, the variations in WCFs by type of cooling technology, prime mover technology, and by region were addressed. The results show that WCFs for electricity generation vary significantly by region. Finally, the generation-weighted average WCFs of thermoelectricity and hydropower are 1.25 (range of 0.18–2.0) and 16.8 (range of 0.67–1194) L/kWh, respectively, and the generation-weighted average WCF by the U.S. generation mix in 2015 is estimated at 2.18 L/kWh.

13 HYDRO ENERGY↗
DOE OSTI2024

Development of a SnO 2 -based 44 Ti/ 44 Sc generator for medical applications

Towards application of 44 Sc for diagnostic nuclear medicine, a 44 Ti/ 44 Sc generator based on an inorganic resin has been evaluated. Unlike other radionuclide generators used for medical applications, the long-term retention of the parent 44 Ti is vital due to its long half life. In this work, tin dioxide (SnO 2 ), a robust inorganic-based resin, has been synthesized and used as the stationary phase for a 44 Ti/ 44 Sc generator. The sorption behavior of 44 Ti/ 44 Sc was tested on SnO 2 with varying acids, concentrations, and times. Preliminary batch study results showed >88 % 44 Ti retention to the resin at lower acid concentrations (0.05 M HNO 3 and 0.05 M HCl). A pilot generator was evaluated for a year, demonstrating 85.3 ± 2.8 % 44 Sc elution yields and 0.71 ± 0.14 % 44 Ti breakthrough in 5 M HNO 3 . Based on capacity studies, a 7.4 MBq (200 µCi) upscaled generator system was constructed for further evaluation of the SnO 2 resin stability and the efficacy of the eluted 44 Sc for radiolabeling. 44 Sc could be regularly eluted from this generator in 5 M HNO 3 with an overall average radiochemical yield 84.7 ± 9.5 %. Post-elution processing of the 44 Sc with DGA-normal resin removed all 44 Ti present and allowed for high 44 Sc-DOTA labeling yields of 94.2 ± 0.5 %. Overall, SnO 2 has been shown to be a viable material for a 44 Ti/ 44 Sc generator.

07 ISOTOPE AND RADIATION SOURCES↗
DOE OSTI2022

Data-driven modeling of power generation for a coal power plant under cycling

Increased penetration of renewables for power generation has negatively impacted the dynamics of conventional fossil fuel-based power plants. The power plants operating on the base load are forced to cycle, to adjust to the fluctuating power demands. This results in an inefficient operation of the coal power plants, which leads up to higher operating losses. To overcome such operational challenge associated with cycling and to develop an optimal process control, this work analyzes a set of models for predicting power generation. Moreover, the power generation is intrinsically affected by the state of the power plant components, and therefore our model development also incorporates additional power plant process variables while forecasting the power generation. We present and compare multiple state-of-the-art forecasting data-driven methods for power generation to determine the most adequate and accurate model. We also develop an interpretable attention-based transformer model to explain the importance of process variables during training and forecasting. The trained deep neural network (DNN) LSTM model has good accuracy in predicting gross power generation under various prediction horizons with/without cycling events and outperforms the other models for long-term forecasting. The DNN memory-based models show significant superiority over other state-of-the-art machine learning models for short, medium and long range predictions. The transformer-based model with attention enhances the selection of historical data for multi-horizon forecasting, and also allows to interpret the significance of internal power plant components on the power generation. This newly gained insights can be used by operation engineers to anticipate and monitor the health of power plant equipment during high cycling periods.

01 COAL, LIGNITE, AND PEAT↗
DOE OSTI2018

Catalytic generation of methane at 60–100 °C and 0.1–300 MPa from source rocks containing kerogen Types I, II, and III

Low temperature (60 and 100 °C) and long-term (6 months to 5 years) heating of pre-evacuated and sterilized shales and coals containing kerogen Types I (Mahogany Shale), II (Mowry Shale and New Albany Shale), and III (Springfield Coal and Wilcox Lignite) with low initial maturities (vitrinite reflectance Ro 0.39–0.62%) demonstrates that catalytically generated hydrocarbons may explain the occurrence of some non-biogenic natural gas accumulations where insufficient thermal maturity contradicts the conventional thermal cracking paradigm. Extrapolation of the observed rate of catalytic methanogenesis in the laboratory suggests that significant amounts of sedimentary organic carbon can be converted to relatively dry natural gas over tens of thousands of years in sedimentary basins at temperatures as low as 60 °C. Here, our laboratory experiments utilized source rock (shale and coal) chips sealed in gold and Pyrex® glass tubes in the presence of hydrogen-isotopically contrasting waters. Parallel heating experiments applied hydrostatic pressures from 0.1 to 300 MPa. Control experiments constrained the influence of pre-existing and residual methane in closed pores of rock chips that was unrelated to newly generated methane. This study’s experimental methane yields at 60 and 100 °C are 5–11 orders of magnitude higher than the theoretically predicted yields from kinetic models of thermogenic methane generation, which strongly suggests a contribution of catalytic methanogenesis. Higher temperature, longer heating time, and lower hydrostatic pressure enhanced catalytic methanogenesis. No clear relationships were observed between kerogen type or total organic carbon content and methane yields via catalysis. Catalytic methanogenesis was strongest in Mowry Shale where methane yields at 60 °C amounted to ~2.5 μmol per gram of organic carbon after one year of hydrous heating at ambient pressure. In stark contrast to the earlier findings of hydrogen isotopic exchange between water and thermogenic methane in hydrous pyrolysis experiments above 300 °C, the hydrogen isotopic composition of added water exerted limited influence on the δ2H value of methane generated catalytically at low temperatures. We hypothesize that the catalytic sites responsible for methanogenesis are located in hydrophobic microenvironments with limited access to water. The δ13CCH4 values of methane generated catalytically at 60–100 °C range from ~–57.6 to –41.4‰ and are thus similar to typical thermogenic methane (δ13CCH4 >–50‰) and microbially generated methane (<–55‰). Future studies need to evaluate the possibility that clumped isotope characteristics of catalytically generated methane can diagnose the low-temperature regime of catalytic methanogenesis. Furthermore, testing of freshly cored anoxic rocks is needed to determine whether the use of archived, oxygen-exposed rocks in geochemical maturation/catalysis studies introduces artifacts in experimental hydrocarbon yields.

58 GEOSCIENCES↗
DOE OSTI2021

Incorporating point defect generation due to jog formation into the vector density-based continuum dislocation dynamics approach

During plastic deformation of crystalline materials, point defects such as vacancies and interstitials are generated by jogs on moving dislocations. A detailed model for jog formation and transport during plastic deformation was developed within the vector density-based continuum dislocation dynamics framework. Here as a part of this model, point defect generation associated with jog transport was formulated in terms of the volume change due to the non-conservative motion of jogs. Balance equations for the vacancies and interstitials including their rate of generation due to jog transport were also formulated. A two-way coupling between point defects and dislocation dynamics was then completed by including the stress contributed by the eigen-strain of point defects. A jog drag stress was further introduced into the mobility law of dislocations to account for the energy dissipation during point defects generation. A number of test problems and a fully coupled simulation of dislocation dynamics and point defects generation and diffusion were performed. The results show that there is an asymmetry of vacancy and interstitial generation due to the different formation energies of the two types of defects. The results also show that a higher hardening rate and a higher dislocation density are obtained when the point defect generation mechanism is coupled to dislocation dynamics.

36 MATERIALS SCIENCE↗
DOE OSTI2024

CoarsenConf: Equivariant Coarsening with Aggregated Attention for Molecular Conformer Generation

Molecular conformer generation (MCG) is an important task in cheminformatics and drug discovery. The ability to efficiently generate low-energy 3D structures can avoid expensive quantum mechanical simulations, leading to accelerated virtual screenings and enhanced structural exploration. Several generative models have been developed for MCG, but many struggle to consistently produce high-quality conformers for meaningful downstream applications. To address these issues, we introduce CoarsenConf, which coarse-grains molecular graphs based on torsional angles and integrates them into an SE(3)-equivariant hierarchical variational autoencoder. Through equivariant coarse-graining, we aggregate the fine-grained atomic coordinates of subgraphs connected via rotatable bonds, creating a variable-length coarse-grained latent representation. Our model uses a novel aggregated attention mechanism to restore fine-grained coordinates from the coarse-grained latent representation, enabling efficient generation of accurate conformers. Furthermore, we evaluate the chemical and biochemical quality of our generated conformers on multiple downstream applications, including property prediction and large-scale oracle-based protein docking. Overall, CoarsenConf generates more accurate conformer ensembles compared to prior generative models.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2024

Mixing of the Connecticut River Plume During Ambient Flood Tides: Spatial Heterogeneity and Contributions of Bottom–Generated and Interfacial Mixing

The Connecticut River plume is influenced by energetic ambient tides in the Long Island Sound receiving waters. The objectives of this modeling study are (a) characterizing the spatial heterogeneity of turbulent buoyancy fluxes, (b) partitioning turbulent buoyancy fluxes into bottom-generated and interfacial shear contributions, and (c) quantifying contributions to plume-integrated mixing within the tidal plume. The plume formed during ambient flood tides under low river discharge, spring tides, and no winds is analyzed. Turbulent buoyancy fluxes (B) and depth-integrated B through the plume (Bd) are characterized by pronounced spatial heterogeneity. Strong mixing (Bd ~ 10 –5 -10 –4 m 3 /s 3 ) occurs near the mouth, in the nearfield plume turning region, over shoals, and nearshore shallow areas. Low to moderate mixing (Bd ~ 10 –8 -10 –6 m 3 /s 3 ) occupies half the plume. Buoyancy fluxes are first partitioned based on the depth of the shear stress minimum between plume-generated and bottom-generated shear maxima. Four other tested partitioning methods are based on open channel flow and stratified shear flow parameterizations. Interfacial and bottom-generated shear contribute to different areas of intense and moderate mixing. All methods indicate a significant plume mixing role for bottom-generated mixing, but interfacial mixing is a bigger contributor. Plume-integrated total and interfacial mixing peak at max ambient flood and the timing of peak bottom-generated mixing varies among partitioning methods. Two-thirds of the mixing occurs in concentrated intense mixing areas. A parameter space with the ambient tidal Froude number and plume thickness to depth ratio as axes indicates many tidally modulated plumes are moderately to dominantly influenced by bottom-generated tidal mixing.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2020

Generative adversarial networks (GAN) based efficient sampling of chemical composition space for inverse design of inorganic materials

A major challenge in materials design is how to efficiently search the vast chemical design space to find the materials with desired properties. One effective strategy is to develop sampling algorithms that can exploit both explicit chemical knowledge and implicit composition rules embodied in the large materials database. Here, we propose a generative machine learning model (MatGAN) based on a generative adversarial network (GAN) for efficient generation of new hypothetical inorganic materials. Trained with materials from the ICSD database, our GAN model can generate hypothetical materials not existing in the training dataset, reaching a novelty of 92.53% when generating 2 million samples. The percentage of chemically valid (charge-neutral and electronegativity-balanced) samples out of all generated ones reaches 84.5% when generated by our GAN trained with such samples screened from ICSD, even though no such chemical rules are explicitly enforced in our GAN model, indicating its capability to learn implicit chemical composition rules to form compounds. Our algorithm is expected to be used to greatly expand the range of the design space for inverse design and large-scale computational screening of inorganic materials.

36 MATERIALS SCIENCE↗
DOE OSTI2026

Active learning enables generation of molecules that advance the known Pareto front

Although generative models hold promise for discovering molecules with optimized desired properties, they often fail to suggest synthesizable molecules that improve upon the properties of the structures represented in the training distribution. We find that this limitation arises not only from the molecule generation process itself, but also from the poor generalization capabilities of molecular property predictors. We address this challenge by creating a closed-loop molecule generation pipeline with iterative retraining on new quantum chemical simulation data. Compared against static, single-pass generative modeling approaches, only our closed-loop iterative workflow generates molecules with properties extending beyond the training distribution (up to 0.44 standard deviations beyond the original range) and achieves a 79% improvement in out-of-distribution molecule classification accuracy. Furthermore, by conditioning molecular generation on thermodynamic stability data obtained during the iterative loop, the proportion of stable and hence potentially synthesizable molecules generated is 3.5x higher than the next-best model.

Chemistry↗
DOE OSTI2023

A database of hourly wind speed and modeled generation for US wind plants based on three meteorological models

Abstract In 2022, wind generation accounted for ~10% of total electricity generation in the United States. As wind energy accounts for a greater portion of total energy, understanding geographic and temporal variation in wind generation is key to many planning, operational, and research questions. However, in-situ observations of wind speed are expensive to make and rarely shared publicly. Meteorological models are commonly used to estimate wind speeds, but vary in quality and are often challenging to access and interpret. The Plant-Level US multi-model WIND and generation (PLUSWIND) data repository helps to address these challenges. PLUSWIND provides wind speeds and estimated generation on an hourly basis at almost all wind plants across the contiguous United States from 2018–2021. The repository contains wind speeds and generation based on three different meteorological models: ERA5, MERRA2, and HRRR. Data are publicly accessible in simple csv files. Modeled generation is compared to regional and plant records, which highlights model biases and errors and how they differ by model, across regions, and across time frames.

17 WIND ENERGY↗