Search NASA⌕ Search

SEARCH · Search NASA

Results for “Reproduction”

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 55 records · Page 3
All sourcesNASA NTRSDOE OSTI
DOE OSTI2026

Optimizing pressurized-water reactor equilibrium cycle using a novel loading pattern encoding and rule-based genetic crossover operators

This work presents an extended multi-batch approach applied in shuffling scheme optimization for equilibrium cycle for pressurized water reactors using Genetic Algorithms (GAs). A new ruled based GA crossover operator called Inherited Location and Batch (ILB) was introduced to enhance offsprings reproduction efficiency specialized for equilibrium cycle optimization problem. This approach was implemented within the Plant ReLoad Optimization (PRLO) framework and validated using a generic reactor model based on the AP1000 design, with core parameters calculated via the CASMO/SIMULATE software package. The ILB approach is then applied for both single and multi-objective problems in maximizing cycle length and core average exposure while minimizing the average enrichment of the 57 fresh fuel assemblies (FAs) per cycle. The optimal solutions are selected based on their dominance to the objectives from all feasible solutions. This research identified three optimal solutions satisfied safety constraints: The first solution minimizes feed enrichment costs with a cycle length of 338.8 days and core exposure of 25.39 MWd/MT; the second solution extends cycle length to 361.2 days, with the highest core exposure of 26.84 MWd/MT, using 3.75 wt% average fuel enrichment; the third solution balances both objectives with a cycle length of 349.6 days, core exposure of 25.82 MWd/MT with a slight enrichment increase compared to the first solution. Collectively, these findings underscore the efficiency and effectiveness of the proposed approach in achieving practical multi-objective optimal equilibrium cycle designs using GAs optimizer.

11 - NUCLEAR FUEL CYCLE AND FUEL MATERIALS↗
DOE OSTI2026

Enabling event-by-event precision in γ-ray cascades for neutron-induced reactions

Neutron-induced γ-ray spectra provide key inputs for modern active interrogation applications. A precise modeling of the nuclear reaction and subsequent emission of γ rays is challenging and often impossible due to limitations on evaluated data file formats and nuclear transport simulation codes. We present a framework that addresses these challenges by combining experimental data and reaction-model calculation outputs into an extended candidate version of the Generalized Nuclear Data Structure (GNDS) file, the successor format for the legacy Evaluated Nuclear Data File (ENDF-6). This proposed GNDS hierarchical format contains all the necessary ingredients for inline γ-ray cascade reproduction with event-by-event precision, including continuum–continuum and continuum–discrete transitions following neutron-capture and inelastic neutron scattering reactions. Cascade-event generation based on our approach demonstrates improved energy conservation on an event-by-event basis and permits the use of γ-γ coincidences in applications. This work offers, for the first time, a method to generate neutron-capture and inelastic neutron-scattering γ-ray cascades where energy conservation, correlations, and experimental primaries are fully accounted for.

73 NUCLEAR PHYSICS AND RADIATION PHYSICS↗
DOE OSTI2025

Phylogenomic insights into the taxonomy, ecology, and mating systems of the lorchel family Discinaceae (Pezizales, Ascomycota)

Lorchels, also known as false morels (Gyromitra sensu lato), are iconic due to their brain-shaped mushrooms and production of gyromitrin, a deadly mycotoxin. Molecular phylogenetic studies have hitherto failed to resolve deep-branching relationships in the lorchel family, Discinaceae, hampering our ability to settle longstanding taxonomic debates and to reconstruct the evolution of toxin production. We generated 75 draft genomes from cultures and ascomata (some collected as early as 1960), conducted phylogenomic analyses using 1542 single-copy orthologs to infer the early evolutionary history of lorchels, and identified genomic signatures of trophic mode and mating-type loci to better understand lorchel ecology and reproductive biology. Our phylogenomic tree was supported by high gene tree concordance, facilitating taxonomic revisions in Discinaceae. We recognized 10 genera across two tribes: tribe Discineae (Discina, Maublancomyces, Neogyromitra, Piscidiscina, and Pseudodiscina) and tribe Gyromitreae (Gyromitra, Hydnotrya, Paragyromitra, Pseudorhizina, and Pseudoverpa); Piscidiscina was newly erected and 26 new combinations were formalized. Paradiscina melaleuca and Marcelleina donadinii formed their own family-level clade sister to Morchellaceae, which merits further taxonomic study. Genome size and CAZyme content were consistent with a mycorrhizal lifestyle for the truffle species (Hydnotrya spp.), whereas the other Discinaceae genera possessed genomic properties of a saprotrophic habit. Lorchels were found to be predominantly heterothallic-either MAT1-1 or MAT1-2-but a single occurrence of colocalized mating-type idiomorphs indicative of homothallism was observed in Gyromitra esculenta strain CBS101906 and requires additional confirmation and follow-up study. Lastly, we confirmed that gyromitrin has a phylogenetically discontinuous distribution, having been detected exclusively in two distantly related genera (Gyromitra and Piscidiscina) belonging to separate tribes. Our genomic dataset will facilitate further investigations into the gyromitrin biosynthesis genes and their evolutionary history. With additional sampling of Geomoriaceae and Helvellaceae-two closely related families with no publicly available genomes-these data will enable comprehensive studies on the independent evolution of truffles and ecological diversification in an economically important group of pezizalean fungi.

Dirks, Alden C↗
DOE OSTI2025

Python Library for Monte Carlo Simulations with Ab Initio and Machine-Learned Interatomic Potentials

There is a growing need in the simulation community for software that provides a transparent, reproducible, usable, and extensible (TRUE) Monte Carlo (MC) simulation framework employing energies from ab initio methods and machine-learning interatomic potentials (MLIPs). We introduce a Python library (ASE-MC) that adds Monte Carlo functionality to the Atomic Simulation Environment (ASE) package. Now, we can combine the powerful tools used to build systems and perform ab initio and MLIP in ASE with MC simulation algorithms to sample the configurational space with a concise Python script. After presenting the design philosophy, we demonstrate the flexibility of our approach using selected examples. These example simulations include liquid water described with a message-passing MLIP in the canonical and isothermal–isobaric ensembles, sampling the characteristic dihedral angle of biphenyl and comparing an MLIP to first-principles calculations, and a grand canonical Monte Carlo simulation of ammonia adsorption on Pt(111). These examples showcase the main features of the software, which include flexibility in the choice of ab initio or MLIP engine, ab initio or MLIP grand canonical MC with cavity bias insertions and deletions, the ability to add custom MC moves to the move set, and how users can condense complex MC workflows into a single Python script. Finally, this library serves as a framework for reproducible Monte Carlo simulations, facilitating easy reproduction of the work and application to new systems.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2024

Selecting Appropriate Model Complexity: An Example of Tracer Inversion for Thermal Prediction in Enhanced Geothermal Systems

Abstract A major challenge in the inversion of subsurface parameters is the ill‐posedness issue caused by the inherent subsurface complexities and the generally spatially sparse data. Appropriate simplifications of inversion models are thus necessary to make the inversion process tractable and meanwhile preserve the predictive ability of the inversion results. In this study, we investigate the effect of model complexity on fracture aperture inversion and thermal performance prediction in a field‐scale EGS model. Principal component analysis was used to map the aperture field to a low‐dimensional latent space. The complexity of the inversion model was quantitatively represented by the percentage of total variance in the original aperture fields preserved by the latent space. Tracer, pressure and flow rate data were used to invert for fracture aperture through an ensemble‐based inversion method, and the inferred aperture field was used to predict thermal performance. With an over‐simplified aperture model, ensemble collapse occurred. The inverted aperture models failed to resolve necessary flow and transport features, leading to a biased thermal performance prediction. A complex aperture model involved excessive features and was prone to overinterpreting the inversion data. Both the tracer/pressure/flow rate data reproduction and thermal prediction showed significant uncertainties, making it difficult to properly estimate long‐term thermal performance. Fortunately, our results indicate that there exists an appropriate model complexity which can simultaneously match inversion data and predict thermal performance with an acceptable uncertainty. The quality of the fit of tracer data appears to be a useful indicator of such an appropriate model complexity.

15 GEOTHERMAL ENERGY↗
DOE OSTI2024

Summertime Continental Shallow Cumulus Cloud Detection Using GOES‐16 Satellite and Ground‐Based Ceilometer at North Alabama

Abstract Accurate simulations of boundary layer cloud processes remain challenging in Earth system modeling. Observations are essential to evaluate and improve models of such processes. This study introduces a comprehensive validation framework for a satellite‐based detection algorithm of continental shallow cumulus (ShCu) clouds during the daytime, which was initially developed using ground‐based observations of stereo cameras at the Department of Energy Atmospheric Radiation Measurement (ARM) Southern Great Plains site (J. Tian et al., 2021, https://doi.org/10.3390/rs13122309 , 2022, https://doi.org/10.1029/2021gl097070 ). To validate this algorithm, the framework employs ground‐based ceilometer measurements from North Alabama (NA) where ShCu populations are prevalent. This study first generates clear‐sky surface reflectance maps at NA and identifies ShCu pixels with a detection threshold using Geostationary Operational Environmental Satellite (GOES) reflectance data. The obtained cloud fractions (CFs) are then compared against CFs from a ground‐based ceilometer, considering factors such as observed area differences, satellite parallax issue, and systematic biases. We found that with a detection threshold (∆R) of 0.05, the ShCu detection algorithm is effective for NA, enabling the reproduction of hourly ShCu CFs using GOES. Our framework is straightforward and easily repeatable to evaluate the effectiveness of a ∆R threshold for detecting ShCu clouds in various geographic regions where ceilometers are deployed. This satellite detection of ShCu provides a crucial regional context for ground‐based measurements, facilitating the tracking of convection initiation and its coupling with land surface conditions. Integrating localized ground‐based and regional satellite data will enhance our ability to conduct thorough studies of cloud morphology and land‐atmosphere interactions in North Alabama.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2024

Many-body enhancement of high-harmonic generation in monolayer MoS2

Abstract Many-body effects play an important role in enhancing and modifying optical absorption and other excited-state properties of solids in the perturbative regime, but their role in high harmonic generation (HHG) and other nonlinear response beyond the perturbative regime is not well-understood. We develop here an ab initio many-body method to study nonperturbative HHG based on the real-time propagation of the non-equilibrium Green’s function with the GW self energy. We calculate the HHG of monolayer MoS 2 and obtain good agreement with experiment, including the reproduction of characteristic patterns of monotonic and nonmonotonic harmonic yield in the parallel and perpendicular responses, respectively. Here, we show that many-body effects are especially important to accurately reproduce the spectral features in the perpendicular response, which reflect a complex interplay of electron-hole interactions (or exciton effects) in tandem with the many-body renormalization and Berry curvature of the independent quasiparticle bandstructure.

36 MATERIALS SCIENCE↗
DOE OSTI2024

Growth rate as a link between microbial diversity and soil biogeochemistry

The growth rate of a microorganism is a simple yet profound way to quantify its impact on the world. The absolute growth rate of a microbial population reflects rates of resource assimilation, biomass production, and element transformation, some of the many ways that organisms affect Earth’s ecosystems and climate. Microbial fitness in the environment depends on the ability to reproduce quickly when conditions are favorable and adopt a survival physiology when conditions worsen, which cells coordinate by adjusting their relative growth rate. At the population level, relative growth rate is a sensitive metric of fitness, linking survival and reproduction to the ecology and evolution of populations. Techniques combining ‘omics and stable isotope probing enable sensitive measurements of growth rates of microbial assemblages and individual taxa in soil. Microbial ecologists can explore how the growth rates of taxa with known traits and evolutionary histories respond to changes in resource availability, environmental conditions, and interactions with other organisms. We anticipate that quantitative and scalable data on the growth rates of soil microorganisms, coupled with measurements of biogeochemical fluxes, will allow scientists to test and refine ecological theory and advance process-based models of carbon flux, nutrient uptake, and ecosystem productivity. Finally, measurements of in situ microbial growth rates provide insights into the ecology of populations and can be used to quantitatively link microbial diversity to soil biogeochemistry.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2026

Phenogenomics reveals the ecology and evolution of Trichoderma fungi for sustainable agriculture

Trichoderma fungi support sustainable agriculture by suppressing plant diseases and improving crop performance. However, emerging pathogenicity of Trichoderma warrants further ecological and genetic characterization. Here we used machine learning to correlate genomic data from 37 Trichoderma strains with over 140 phenotypic traits, spanning metabolic versatility, biotic interactions, stress tolerance and reproductive strategies. We determined Trichoderma to be an ancient, genetically cohesive and physiologically diverse genus with spores capable of germination in water and dispersal via air and water droplets. Metabolic preferences indicate universal adaptation to mycoparasitism and to niches like arboreal microbial mats, alongside broader saprotrophic versatility. Our analyses are consistent with character displacement among close relatives and convergent evolution in distant lineages, with both processes shaping ecological plasticity and traits including dispersal modes, terrestrialization or endophytism. Our findings reveal that while some Trichoderma species show traits of biosafety concern, its vast ecophysiological diversity enables the development of safe, targeted bioeffectors.

Steindorff, Andrei S. [USDOE Joint Genome Institut↗
DOE OSTI2025

Induced protein expression in Leptospira spp. and its application to CRISPR/Cas9 mutant generation

Abstract Expanding the genetic toolkit for Leptospira spp. is a crucial step toward advancing our understanding of the biology and virulence of these atypical bacteria. Pathogenic Leptospiraare responsible for over 1 million human leptospirosis cases annually and significantly impact domestic animals. Bovine leptospirosis causes substantial financial losses due to abortion, stillbirths, and suboptimal reproductive performance. The advent of the CRISPR/Cas9 system has marked a turning point in genetic manipulation, with applications across multiple Leptospira species. However, incorporating controlled protein expression into existing genetic tools could further expand their utility. We developed and demonstrated the functionality of IPTG-inducible heterologous protein expression in Leptospira spp. This system was applied for regulated expression of dead Cas9 (dCas9) to generate knockdown mutants, and Cas9 to produce knockout mutants by inducing double-strand breaks (DSB) into desired targets. IPTG-induced dCas9 expression enabled validation of essential genes and non-coding RNAs. Additionally, IPTG-controlled Cas9 expression combined with a constitutive non-homologous end-joining (NHEJ) system allowed for successful recovery of knockout mutants, even in the absence of IPTG. These newly controlled protein expression systems will advance studies on the basic biology and virulence ofLeptospira, as well as facilitate knockout mutant generation for improved veterinary vaccines.

Science & Technology - Other Topics↗
DOE OSTI2024

A portable and reusable sensor system based on graphene for real-time and sensitive detection of lead ions in water

Long-term exposure to Pb 2+ can cause irreversible damage to the nervous, cardiovascular, and reproductive systems. Therefore, developing a fast and sensitive detection system capable of monitoring minuscule concentrations of Pb 2+ is essential. In this study, we demonstrated a fully portable sensor system enabling rapid, sensitive, and real-time monitoring of Pb 2+ . The sensor system adopted the remote-gate field-effect transistor (RGFET) detection scheme and was easy to operate, even for non-experts. The sensor system comprised two printed circuit boards (PCBs): a sensor PCB with a remote-gate electrode and an analyzer PCB with a metal-oxide-semiconductor field-effect transistor (MOSFET) transducer and peripheral electronics to manage sensor signals. To achieve a high sensitivity for Pb 2+ , we utilized graphene ink drop-casted on the sensor PCB as a sensing membrane. The graphene film was easy to deposit and remove, enabling the sensor PCB to be reused multiple times. The sensor system was further linked to a smartphone application that instantly monitors the sensor response, allowing for rapid point-of-use detection. The sensor exhibited a high sensitivity of 21.7% when the limit of detection (LOD) value of 1 nM (∼0.2 ppb) was detected, and the typical detection time for each sample was approximately 60 seconds. This portable sensor system advances sensing technologies and could potentially supplement expensive, laborious conventional sensing equipment.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2024

Machine learning based unfolding of x-ray spectra from filter stack spectrometer data

We demonstrate the application of neural networks to perform x-ray spectra unfolding from data collected by filter stack spectrometers. A filter stack spectrometer consists of a series of filter-detector pairs, where the detectors behind each filter measure the energy deposition through each layer as photo-stimulated luminescence (PSL). The network is trained on synthetic data, assuming x-rays of energies < 1 MeV and of two different distribution functions (Maxwellian and Gaussian) and the corresponding measured PSL values obtained from five different filter stack spectrometer designs. Predicted unfolds of single distributions are near identical reproductions of the ground truth spectra, with differences in the values lower than 20% at the higher energy end in some cases. The neural network has also demonstrated robustness to experimental measurement errors of < 5% and some capability of performing unfolds for linear combinations of the two distributions without previous training. The network can perform unfolds at rates > 1 Hz, ideal for application to some high-repetition-rate systems.

47 OTHER INSTRUMENTATION↗
DOE OSTI2025

Validation of a comprehensive first-principles-based framework for predicting the performance of future stellarators

This paper presents the validation of the GENE-KNOSOS-Tango framework for recovering both the steady-state plasma profiles in the considered radial domain and selected turbulence trends in a stellarator. This framework couples the gyrokinetic turbulence code GENE, the neoclassical transport code KNOSOS, and the transport solver Tango in a multi-timescale simulation feedback loop. Ion-scale kinetic-electron and electron-scale adiabatic-ion flux-tube simulations were performed to evolve the density and temperature profiles for four OP1.2b W7-X scenarios. The simulated density and temperature profiles showed good agreement with the experimental data using a reasonable set of boundary conditions. Equally important was the reproduction of observed trends for several turbulence properties, such as density fluctuations and turbulent heat diffusivities. Key effects were also touched upon, such as electron-scale turbulence and the neoclassical radial electric field shear. The validation of the GENE-KNOSOS-Tango framework enables credible predictions of physical phenomena in stellarators and reactor performance based on a given set of edge parameters.

Gyrokinetic simulations↗
DOE OSTI2025

Audible enclaves crafted by nonlinear self-bending ultrasonic beams

Delivering audible content to a targeted listener without disturbing others is paramount in audio engineering. However, achieving this goal has long been challenging due to the diffraction of low-frequency (long-wavelength) audio waves in linear acoustics. Here, we introduce an approach for creating remote audio spots, dubbed audible enclaves, by harnessing the local nonlinear interaction of two self-bending ultrasonic beams with distinct spectra. The self-bending ultrasonic beams created by acoustic metasurfaces, though inaudible, can bypass obstacles such as human heads. At their intersection behind obstacles, highly localized audible enclaves are formed due to the local nonlinear interactions. Additionally, we demonstrate the ultrabroadband capabilities of our metasurface-based implementation both numerically and experimentally, spanning from 125 Hz to 4 kHz (6 octave bands), covering the majority of the audible frequency range. The practicality of our proposed technique is underscored by its compact implementation size (0.16 m, equivalent to 0.06 wavelengths at 125 Hz), as well as its robust performance under wideband transient audio signal excitation and in a common room with reverberations. Our proposed audible enclaves hold significant potential for various applications in advanced audio engineering, including private speech communications, immersive spatial audio reproduction, and high-resolution sound/quiet zone control.

Science & Technology - Other Topics↗
DOE OSTI2025

Apomixis in Farmers’ Fields: Overview, Case Studies from Forage Grasses and Considerations for Future Apomictic Crops

Apomixis occurs naturally in several commercially important species from diverse plant families. While in some of these species apomixis is yet to be exploited in breeding schemes aimed at fixing heterosis, genetic progress and cultivar development, in other species apomixis has been integrated at different stages of breeding. Some of the most relevant examples come from the subfamily Panicoideae, the second largest subfamily of the Poaceae, and are the main focus of this review. The subfamily encompasses many tropical and sub-tropical grasses and grains of worldwide economic importance. Apomictic tropical forages are prime examples of how apomixis can be used and exploited in the development of marketable cultivars, which are essential to the meat and milk production industries globally. The main commercial forages used as grass pastures covering millions of hectares in tropical and sub-tropical regions are polyploids exhibiting gametophytic apomixis that belong to the genus Urochloa spp. (brachiariagrasses) and to the species Megathyrsus maximus (guineagrass). Buffel grass (Cenchrus ciliaris) and Paspalum spp. are other important apomictic forages bred and used in these regions. Breeding involves large germplasm collections from the centers of origin of the species, and for most of them, sexually reproducing diploid plants have been found. Chromosomically duplicated plants that maintain sexual reproduction are used in crosses with apomictic genotypes for the development and selection of cultivars to be marketed or used as progenitors in subsequent breeding cycles. The peculiarities of each genus/species breeding programs, the cultivars obtained from these programs, and the impact of use of marker assisted selection in cultivar development are presented. In addition, the test or implementation of new technologies such as high throughput phenotyping, and the use of machine learning methods for trait prediction and genomic selection are positively impacting the selection and speed of development of new polyploid apomictic cultivars. Furthermore, genetic transformation techniques, including genome editing, provide an additional layer for design of tailor-made, customer-oriented cultivars.

Cenchrus↗
DOE OSTI2025

Natural variation in growth and yield to waterlogging across climate-diverse pennycress accessions

Many winter annual crops, such as pennycress ( Thlaspi arvense L.), are subjected to heavy precipitation events during their growing season. Therefore, it is essential to identify pennycress accessions with natural variation in flooding resilience. We used climate modeling data to assess spring soil moisture levels in the geographic origins of 471 natural pennycress accessions. We selected 34 accessions with variation in predicted soil moisture and tested survivability under prolonged waterlogging at the rosette stage. It took seven weeks for the first accessions to die, indicating that pennycress is hardy to prolonged waterlogging at the vegetative stage. Furthermore, we chose ‘susceptible’ and ‘tolerant’ accessions to waterlog for one week at the reproductive stage, the growth stage aligned with spring rainfall. Six accessions had significantly reduced seed weight at maturity and two had minimal impacts on growth and seed yield after waterlogging and can be further explored for adaptive traits.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2024

Reconstruction and interpretation of ionization asymmetry in magnetic confinement via synthetic diagnostics

Abstract Strong poloidal refueling asymmetry in the DIII-D tokamak is inferred from line radiation measurements. Synthetic diagnostics in neutral transport modeling coupled to gyrokinetic simulations illuminate implications for the plasma flow profile in the scrape-off layer of single-null beam-driven discharges. Recycling occurs primarily either on the inner or outer divertor legs, depending on the toroidal magnetic field direction. By reversing the toroidal magnetic field, the observed line radiation asymmetry is nearly eliminated or reversed. It is determined that, while relatively simple physics can describe the observed ionization asymmetry, predicting the overall brightness of the hydrogenic Lyman- α signal requires detailed simulation of the plasma and resulting turbulence. To this end, kinetic plasma simulations fully coupled to comprehensive neutral transport calculations—a novel capability—provide first-principles reproduction of Lyman- α observations on DIII-D.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗
DOE OSTI2024

Embedded FPGA developments in 130 nm and 28 nm CMOS for machine learning in particle detector readout

Embedded field programmable gate array (eFPGA) technology allows the implementation of reconfigurable logic within the design of an application-specific integrated circuit (ASIC). This approach offers the low power and efficiency of an ASIC along with the ease of FPGA configuration, particularly beneficial for the use case of machine learning in the data pipeline of next-generation collider experiments. An open-source framework called "FABulous" was used to design eFPGAs using 130 nm and 28 nm CMOS technology nodes, which were subsequently fabricated and verified through testing. The capability of an eFPGA to act as a front-end readout chip was assessed using simulation of high energy particles passing through a silicon pixel sensor. A machine learning-based classifier, designed for reduction of sensor data at the source, was synthesized and configured onto the eFPGA. A successful proof-of-concept was demonstrated through reproduction of the expected algorithm result on the eFPGA with perfect accuracy. Finally, further development of the eFPGA technology and its application to collider detector readout is discussed.

47 OTHER INSTRUMENTATION↗