Search NASA⌕ Search

SEARCH · Search NASA

Results for “Trade Tree”

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 37 records · Page 2

Improving leaf spring phenology modelling for temperate tree species: An integration of the Farquhar–Medlyn photosynthesis model with the optimality‐based approach

Spring leaf phenology in temperate tree species is highly sensitive to climate change and significantly affects plant photosynthetic performance, resource utilization, competition and trophic interactions, thereby impacting various ecosystem functions. Although optimality-based (OPT) approaches for modelling spring phenology are increasingly recognized, the optimal representation of the underlying principle (balancing photosynthesis gains with chilling risks) remains controversial. Here, we integrated a coupled Farquhar–Medlyn photosynthesis model into an existing OPT model, and termed the resulting model R-OPT, and evaluated its performance using the PEP725 dataset, which includes 409,144 site-species-year records from across Europe. Our results show that R-OPT outperforms both the default OPT and non-optimality-based models (e.g. the chilling-forcing trade-off and growing degree day models). This improved performance is consistent within and across five focal tree species but varies by region: R-OPT excels in lowland, moist environments but is less effective in high-altitude, cold, and dry areas, possibly due to an incomplete representation of environmental constraints on photosynthetic carbon gain in these regions. Our research advances leaf spring phenology modelling by emphasizing an optimality principle that balances photosynthetic carbon gain with chilling risk, improving the representation of plant photosynthesis processes and enhancing understanding of environmental factors influencing phenology in the context of climate change.

coupled Farquhar–Medlyn photosynthesis model↗

One hundred years into the study of ecotypes, new advances are being made through large-scale field experiments in perennial plant systems

A hundred years after Turesson first clearly described how locally adaptive variation is distributed within species, plant biologists are making major breakthroughs in our understanding of mechanisms underlying adaptation from local populations to the scale of continents. Although the genetics of local adaptation has typically been studied in smaller reciprocal transplant experiments, here it is being evaluated with whole genomes in large-scale networks of common garden experiments with perennial switchgrass and poplar trees. These studies support the hypothesis that a complex combination of loci, both with and without adaptive trade-offs, underlies local adaptation and that hybridization and adaptive introgression play a key role in the evolution of these species. Future studies incorporating high-throughput phenotyping, gene expression, and modeling will be used to predict responses of these species to climate change.

Trade-off↗

Efficient and Flexible Hierarchical Data Layouts for a Unified Encoding of Scalar Field Precision and Resolution

To address the problem of ever-growing scientific data sizes making data movement a major hindrance to analysis, we introduce a novel encoding for scalar fields: a unified tree of resolution and precision, specifically constructed so that valid cuts correspond to sensible approximations of the original field in the precision-resolution space. Furthermore, we introduce a highly flexible encoding of such trees that forms a parameterized family of data hierarchies. We discuss how different parameter choices lead to different trade-offs in practice, and show how specific choices result in known data representation schemes such as zfp[52], idx[58], and jpeg2000 [76]. Lastly, we provide system-level details and empirical evidence on how such hierarchies facilitate common approximate queries with minimal data movement and time, using real-world data sets ranging from a few gigabytes to nearly a terabyte in size. Experiments suggest that our new strategy of combining reductions in resolution and precision is competitive with state-of-the-art compression techniques with respect to data quality, while being significantly more flexible and orders of magnitude faster, and requiring significantly reduced resources.

97 MATHEMATICS AND COMPUTING↗

Tropical Tree Crop Simulation with a Process-Based, Daily Timestep Simulation Model (ALMANAC): Description of Model Adaptation and Examples with Coffee and Cocoa Simulations

Coffee (Coffea species) and Cocoa (Theobroma cacao) are important cash crops grown in the tropics but traded globally. This study was conducted to apply the ALMANAC model to these crops for the first time, and to test its ability to simulate them under agroforestry management schemes and varying precipitation amounts. To create this simulation, coffee was grown on a site in Kaua’i, Hawai’i, USA, and cocoa was grown on a site in Sefwi Bekwai, Ghana. A stand-in for a tropical overstory tree was created for agroforestry simulations using altered parameters for carob, a common taller tropical tree for these regions. For both crops, ALMANAC was able to realistically simulate yields when compared to the collected total yield data. On Kaua’i, the mean simulated yield was 2% different from the mean measured yield, and in all three years, the simulated values were within 10% of the measured values. For cocoa, the mean simulated yield was 3% different from the mean measured yield and the simulated yield was within 10% of measured yields for all four available years. When precipitation patterns were altered, in Ghana, the wetter site showed lower percent changes in yield than the drier site in Hawai’i. When agroforestry-style management was simulated, a low Leaf Area Index (LAI) of the overstory showed positive or no effect on yields, but when LAI climbed too high, the simulation was able to show the detrimental effect this competition had on crop yields. These simulation results are supported by other literature documenting the effects of agroforestry on tropical crops. This research has applied ALMANAC to new crops and demonstrated its simulation of different management and environmental conditions. The results show promise for ALMANAC’s applicability to these scenarios as well as its potential to be further tested and utilized in new circumstances.

60 APPLIED LIFE SCIENCES↗

Distinguishing Orbiting and Infalling Dark Matter Particles with Machine Learning

Dark matter halos are typically defined as spheres that enclose some overdensity, but these sharp, somewhat arbitrary boundaries introduce nonphysical artifacts such as backsplash halos, pseudo-volution, and an incomplete accounting of halo mass. A more physically motivated alternative is to define halos as the collection of particles that are physically orbiting within their potential well. However, existing methods to classify particles as orbiting or infalling suffer from trade-offs between accuracy, computational cost, and generalizability across cosmologies. We present an efficient, yet accurate, supervised machine learning approach using decision trees. The classification is based on only the particle radii and velocities at two epochs. Compared to detailed analysis of particle trajectories, we find that our model matches the classification of 97% of particles. Consequently, we are able to quickly and accurately reproduce the density profiles of the orbiting and infalling components out to many virial radii. We demonstrate that our model generalizes to a significantly different cosmology that lies outside the training data set. We make publicly available both our final model and the code to train similar models.

79 ASTRONOMY AND ASTROPHYSICS↗

Tree-mendous Timber Evaluation

Funded and administered by NASA, the Affiliated Research Center (ARC) program transfers geospatial technologies from the Space Agency and participating universities to commercial companies, non-profit and trade organizations, and tribal governments. The origins of the ARC program date back to 1988, when NASA's Stennis Space Center initiated the Visiting Investigator Program to bring industry closer to spatial information technologies. The success of this trial program led to an expansion into the ARC program, whose goal is to enhance competitiveness of U.S. industries through more efficient use of remote sensing and related technologies. NASA's ARC program served as the foundation for the development of International Hardwood Resources, which then grew into Falcon Informatics with the acquisition of a technology from a European software company and a change of business models. Doylestown, Pennsylvania-based Falcon Informatics is now a world-leading information services company that combines in-depth timber industry experience with state-of-the-art software to serve the needs of national governments, international paper companies, and timber-investment management organizations.

Source record↗

Proposed reliability cost model

The research investigations which were involved in the study include: cost analysis/allocation, reliability and product assurance, forecasting methodology, systems analysis, and model-building. This is a classic example of an interdisciplinary problem, since the model-building requirements include the need for understanding and communication between technical disciplines on one hand, and the financial/accounting skill categories on the other. The systems approach is utilized within this context to establish a clearer and more objective relationship between reliability assurance and the subcategories (or subelements) that provide, or reenforce, the reliability assurance for a system. Subcategories are further subdivided as illustrated by a tree diagram. The reliability assurance elements can be seen to be potential alternative strategies, or approaches, depending on the specific goals/objectives of the trade studies. The scope was limited to the establishment of a proposed reliability cost-model format. The model format/approach is dependent upon the use of a series of subsystem-oriented CER's and sometimes possible CTR's, in devising a suitable cost-effective policy.

Delionback, L. M.↗

The Kepler Mission: A Search for Terrestrial Planets - Development Status

We have embarked on a mission to detect terrestrial planets. The space mission has been optimized to search for earth-size planets (0.5 to 10 earth masses) in the habitable zone (HZ) of solar-like stars. Given this design, the mission will necessarily be capable of not only detecting Earth analogs, but a wide range of planetary types and characteristics ranging from Mercury-size objects with orbital periods of days to gas-giants in decade long orbits that have undeniable signatures even with only one transit detected. The mission is designed to survey the full range of spectral-type dwarf stars. The approach is to detect the periodic signal of transiting planets. Three or more transits of a star exceeding a combined threshold of eight sigma with a statistically consistent period, brightness change and duration provide a rigorous method of detection. From the relative brightness change the planet size can be calculated. From the period the orbital size can be calculated and its location relative to the HZ determined. Presented here are: the mission goals, the top level system design requirements derived from these goals that drive the flight system design, a number of the trades that have lead to the mission concept, expected photometric performance dependence on stellar brightness and spectral type based on the system 'noise tree' analysis. Updated estimates are presented of the numbers of detectable planets versus size, orbit, stellar spectral type and distances based on a planet frequency hypothesis. The current project schedule and organization are given.

Koch, David↗

Distinct xylem responses to acute vs prolonged drought in pine trees

Increasing dryness challenges trees’ ability to maintain water transport to the leaves. Most plant hydraulics models use a static xylem response to water stress. Yet, in reality, lower soil moisture and warmer temperatures during growing seasons feed back onto xylem development. In turn, adjustments to water stress in the newly built xylem influence future physiological responses to droughts. In this study, we investigate the annual variation of anatomical traits in branch xylem in response to different soil and atmospheric moisture conditions and tree stress levels, as indicated by seasonal predawn leaf water potential (??L,pd). We used a 6-year field experiment in southwestern USA with three soil water treatments applied to Pinus edulis Engelm trees—ambient, drought (45% rain reduction) and irrigation (15–35% annual water addition). All trees were also subject to a natural 1-year acute drought (soil and atmospheric) that occurred during the experiment. The irrigated trees showed only moderate changes in anatomy-derived hydraulic traits compared with the ambient trees, suggesting a generally stable, well-balanced xylem structure under unstressed conditions. The artificial prolonged soil drought increased hydraulic efficiency but lowered xylem construction costs and decreased tracheid implosion safety ((t/b)2), suggesting that annual adjustments of xylem structure follow a safety–efficiency trade-off. The acute drought plunged hydraulic efficiency across all treatments. The combination of acute and prolonged drought resulted in vulnerable and inefficient new xylem, disrupting the stability of the anatomical trade-off observed in the rest of the years. The xylem hydraulic traits showed no consistent direct link to ??L,pd. In the future, changes in seasonality of soil and atmospheric moisture are likely to have a critical impact on the ability of P. edulis to acclimate its xylem to warmer climate. Furthermore, the increasing frequency of acute droughts might reduce hydraulic resilience of P. edulis by repeatedly creating vulnerable and less efficient anatomical structure.

Guerin, Marceau↗

Allometric relationships and trade‐offs in 11 common M editerranean‐climate grasses

Abstract Biomass allocation in plants is the foundation for understanding dynamics in ecosystem carbon balance, species competition, and plant–environment interactions. However, existing work on plant allometry has mainly focused on trees, with fewer studies having developed allometric equations for grasses. Grasses with different life histories can vary in their carbon investment by prioritizing the growth of specific organs to survive, outcompete co‐occurring plants, and ensure population persistence. Further, because grasses are important fuels for wildfire, the lack of grass allocation data adds uncertainty to process‐based models that relate plant physiology to wildfire dynamics. To fill this gap, we conducted a greenhouse experiment with 11 common California grasses varying in photosynthetic pathway and growth form. We measured plant sizes and harvested above‐ and belowground biomass throughout the life cycle of annual species, while for the establishment stage of perennial grasses to quantify allometric relationships for leaf, stem, and root biomass, as well as plant height and canopy area. We used basal diameter as a reference measure of plant size. Overall, basal diameter is the best predictor for leaf and stem biomass, height, and canopy area. Including height as another predictor can improve model accuracy in predicting leaf and stem biomass and canopy area. Fine root biomass is a function of leaf biomass alone. Species vary in their allometric relationships, with most variation occurring for plant height, canopy area, and stem biomass. We further explored potential trade‐offs in biomass allocation across species between leaf and fine root, leaf and stem, and allocation to reproduction. Consistent with our expectation, we found that fast‐growing plants allocated a greater fraction to reproduction. Additionally, plant height and specific leaf area negatively influenced the leaf‐to‐stem ratio. However, contrary to our hypothesis, there were no differences in root‐to‐leaf ratio between perennial and annual or C 4 and C 3 plants. Our study provides species‐specific and functional‐type‐specific allometry equations for both above‐ and belowground organs of 11 common California grass species, enabling nondestructive biomass assessment in California grasslands. These allometric relationships and trade‐offs in carbon allocation across species can improve ecosystem model predictions of grassland species interactions and environmental responses through differences in morphology.

54 ENVIRONMENTAL SCIENCES↗

A localized ensemble of approximate Gaussian processes for fast sequential emulation

More attention has been given to the computational cost associated with the fitting of an emulator. Substantially less attention is given to the computational cost of using that emulator for prediction. This is primarily because the cost of fitting an emulator is usually far greater than that of obtaining a single prediction, and predictions can often be obtained in parallel. In many settings, especially those requiring Markov Chain Monte Carlo, predictions may arrive sequentially and parallelization is not possible. In this case, using an emulator procedure which can produce accurate predictions efficiently can lead to substantial time savings in practice. In this paper, we propose a global model approximate Gaussian process framework via extension of a popular local approximate Gaussian process (laGP) framework. Our proposed emulator can be viewed as a treed Gaussian process where the leaf nodes are laGP models, and the tree structure is learned greedily as a function of the prediction stream. The suggested method (called leapGP) has interpretable tuning parameters which control the time‐memory trade‐off. One reasonable choice of settings leads to an emulator with a training cost and makes predictions rapidly with an asymptotic amortized cost of .

97 MATHEMATICS AND COMPUTING↗

Process design for recovering rare-earth elements from mine tailings with low rare-earth concentrations via sequential leaching and solvent extraction

Rare earth elements (REEs) are essential for advanced technologies and yet face significant supply chain risks due to their concentrated global production and limited domestic availability. Addressing this challenge requires efficient processes capable of upgrading low-grade secondary resources such as mine tailings. In this study, we developed a novel separation flowsheet that integrates sequential leaching and 2-stage solvent extraction (SX) processes to recover high-purity heavy REEs (HREEs) and light REEs (LREEs) from a simulated mine-tailing concentrate containing 2.4 wt% total REEs (TREEs; 0.6 wt% LREEs and 1.8 wt% HREEs). Sequential leaching with controlled pH adjustment selectively precipitated REEs while retaining the large amount of impurities in the solution, producing an REE-enriched leachate by following leaching processes with roughly twice the REE concentration and half the impurity concentration compared to that of single-step leaching. The optimized SX flowsheet employed Cyanex 572 to extract HREEs and Fe over LREEs, followed by Fe removal using tributyl phosphate (TBP), while the raffinate stream was processed by SX with di(2-ethylhexyl)phosphoric acid (D2EHPA) to recover LREEs under optimized conditions balancing both extraction efficiency and purity. Although increased extractant availability in the organic phase improved LREE recovery, it also increased co-extraction of Ca, underscoring trade-offs in process optimization. Both HREE- and LREE-rich solutions were subsequently precipitated into solid products via oxalate precipitation, resulting in high-purity REE solids containing ∼92.0 wt% HREEs (∼95.7 wt% TREEs) and ∼92.8 wt% LREEs (∼94.0 wt% TREEs). In conclusion, this proof-of-concept study using simulated mine tailings demonstrates a promising approach for upgrading low-grade REE resources, while highlighting the need for future validation with real materials.

Mine tailings↗

Sequential Testing Algorithms for Multiple Fault Diagnosis

In this paper, we consider the problem of constructing optimal and near-optimal test sequencing algorithms for multiple fault diagnosis. The computational complexity of solving the optimal multiple-fault isolation problem is super-exponential, that is, it is much more difficult than the single-fault isolation problem, which, by itself, is NP-hard. By employing concepts from information theory and AND/OR graph search, we present several test sequencing algorithms for the multiple fault isolation problem. These algorithms provide a trade-off between the degree of suboptimality and computational complexity. Furthermore, we present novel diagnostic strategies that generate a diagnostic directed graph (digraph), instead of a diagnostic tree, for multiple fault diagnosis. Using this approach, the storage complexity of the overall diagnostic strategy reduces substantially. The algorithms developed herein have been successfully applied to several real-world systems. Computational results indicate that the size of a multiple fault strategy is strictly related to the structure of the system.

Shakeri, Mojdeh↗

Sequential Test Strategies for Multiple Fault Isolation

In this paper, we consider the problem of constructing near optimal test sequencing algorithms for diagnosing multiple faults in redundant (fault-tolerant) systems. The computational complexity of solving the optimal multiple-fault isolation problem is super-exponential, that is, it is much more difficult than the single-fault isolation problem, which, by itself, is NP-hard. By employing concepts from information theory and Lagrangian relaxation, we present several static and dynamic (on-line or interactive) test sequencing algorithms for the multiple fault isolation problem that provide a trade-off between the degree of suboptimality and computational complexity. Furthermore, we present novel diagnostic strategies that generate a static diagnostic directed graph (digraph), instead of a static diagnostic tree, for multiple fault diagnosis. Using this approach, the storage complexity of the overall diagnostic strategy reduces substantially. Computational results based on real-world systems indicate that the size of a static multiple fault strategy is strictly related to the structure of the system, and that the use of an on-line multiple fault strategy can diagnose faults in systems with as many as 10,000 failure sources.

Shakeri, M.↗

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

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

Ha, Chan Man↗

Higher Wood Density Lowers Feedstock Cost and Has Minimal Impact on Biomass Conversion to Biofuels

Poplar and other woody feedstocks have the potential to provide up to 200 million tons of biomass per year that can be converted to liquid fuels. Most forestry strategies that aim to increase biomass productivity per hectare rely on short rotation plantations of fast-growing varieties. The improvement of the wood density as a key trait itself has largely been overlooked. We evaluated natural variation in wood density across a population of genetically diverse Populus trichocarpa trees grown in a common garden. Wood density varies greatly within this population but is heritable; higher wood density was not systematically associated with reduced growth, challenging assumptions of a trade-off between wood density and biomass accumulation. Furthermore, denser wood led to significant improvements throughout the supply chain including lowering biomass production and transportation costs. Higher density did not correlate with changes in biomass composition. Density did not impact bioconversion in the two feedstock-to-fuel pipelines tested (pretreatment by ionic liquids and fermentation to bisabolene or soaking in aqueous ammonia and fermentation to ethanol) on a representative subset of poplars. These findings highlight wood density as a promising breeding target for accelerating the development of high-yielding, conversion-efficient bioenergy crops and as an avenue for increasing landuse efficiency and reducing biomass transportation cost.

09 BIOMASS FUELS↗

An Intelligent Distributed Ledger Construction Algorithm for IoT

Blockchain is the next generation of secure data management that creates near-immutable decentralized storage. Secure cryptography created a niche for blockchain to provide alternatives to well-known security compromises. However, design bottlenecks with traditional blockchain data structures scale poorly with increased network usage and are extremely computation-intensive. This made the technology difficult to combine with limited devices, like those in Internet of Things networks. In protocols like IOTA, replacement of blockchain's linked-list queue processing with a lightweight dynamic ledger showed remarkable throughput performance increase. However, current stochastic algorithms for ledger construction suffer distinct trade-offs between efficiency and security. This work proposed a machine-learning approach with a multi-arm bandit that resolved these issues and was designed for auditing on limited devices. This algorithm was tested in a reinforcement-learning environment simulating the IOTA ledger's construction with a decision tree. This study showed through regret analysis and experimentation that this approach was secure against impulse manipulation attacks while remaining energy-efficient. Although the IOTA protocol was a pioneer for lightweight distributed ledgers, it is expected that future blockchain protocols will adopt techniques similar to those presented in this work.

multi-arm bandit↗

Modeling In-Space Aborts for NASA Human Exploration Missions

NASA is developing new capabilities to send humans beyond low Earth orbit (LEO) for the first time in several decades with the new Multi-purpose Crew Vehicle (MPCV) Orion spacecraft and Space Launch System (SLS) launch vehicle. As part of these capabilities, NASA is developing means to terminate missions prior to reaching mission destinations in order to save the crew in the event of critical life-threatening failures. This abort capability exists for both ascent and in-space operations. While the risk associated with ascent aborts has been modeled in detail, less has been done in the area of in-space aborts (e.g. Apollo 13). Recent efforts have started to better assess the risk associated with in-space aborts. This paper will describe these efforts. The in-space abort model described in this paper is part of a larger Cross-Program PRA (XPRA) model of exploration missions planned in the next few years to the vicinity of the Moon. The model consists of linked event trees and fault trees and associated rules built using the Systems Analysis Program for Hands-On Integrated Reliability Evaluations (SAPHIRE) tool. This model structure is being built with flexibility in mind in order to perform risk trades and further expansion of the model.

Bigler, Mark A.↗