Engineering Papers⌕ Search

SEARCH · Engineering Papers

Results for “Differential Experiments”

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 1,765 records · Page 98
All sourcesNASA NTRSDOE OSTI
NASA NTRSDate not supplied

Recent Advances in Soft Matter Characterization Capabilities Developed at NASA GRC for Lunar Exploration: Differential Dynamic Microscopy to Spectroscopy to Computer Vision

In 1991, famous French scientist Pierre-Gilles de Genes was awarded Nobel prize for his impactful research in soft matter, more specifically polymers. He is defined as the founding father of soft matter. In his Nobel lecture (https://www.nobelprize.org/uploads/2018/06/gennes-lecture.pdf ) he described soft matter aka complex fluids as materials with two primary features – (a) complexity and (b) flexibility. The sub-categories of soft matter (e.g.- granular materials, polymers, foams, colloids etc.) are defined on the basis of Pierre-Gilles de Gennes’ definition. At NASA GRC, we are pushing the boundaries for fundamental study of soft matter on Lunar Surface. With regard to Lunar surface science, we are focusing on developing capabilities pertaining to granular materials and bio-soft/active matter to facilitate future efforts in ISRU and bio-ISRU capabilities. In order to achieve fundamental goals of soft matter research within the limitations of Lunar environment, the scientific capabilities need to be small, flexible, modular, off the shelf and the focus needs to be more on developing an interdisciplinary capability that leverages the recent growth in AI/ML and Computer Vision to augment our understanding of fundamental science. This strategy would allow us to reduce our resource requirement during launch, installation, and occupied real estate footprint on Lunar surface In this talk, we will go over 3 different capabilities that we have developed in house and in close collaboration – (a) Differential Dynamic Microscopy (DDM), (b) Portable In-situ Chemical Spectroscopy (PICS) and (c) Computer Vision Enabled Observation. At very high level, Differential Dynamic Microscopy (DDM) allows us to study the structure-property-process relation (microrheology) of bio-soft/active matter using optical microscope and improved image analysis capabilities. PICS uses AI/ML-based advanced signal deconvolution and analysis technique that can work with existing portable spectroscopy tools to perform materials analysis (e.g.- granular materials and bio-soft/active matter) inspection on the go. Finally, computer vision enabled analysis allows us to use simple camera images for 3D reconstruction of experimental process and tracking of objects of interest in an experiment. We expect that this detailed process will allow us reach a thorough understanding of soft matter in Lunar environment. The capabilities developed by us will help to validate and establish fundamental understanding in Lunar environment. This will, in turn, allow us to guide future space exploration missions and expand the knowledge base of the scientific and engineering communities.

Suman Sinha Ray↗
NASA NTRSDate not supplied

Recent Advances in Soft Matter Characterization Capabilities Developed at NASA GRC

In 1991, famous French scientist Pierre-Gilles de Genes was awarded Nobel prize for his impactful research in soft matter, more specifically polymers. He is defined as the founding father of soft matter. In his Nobel lecture (https://www.nobelprize.org/uploads/2018/06/gennes-lecture.pdf ) he described soft matter aka complex fluids as materials with two primary features – (a) complexity and (b) flexibility. The sub-categories of soft matter (e.g.- granular materials, polymers, foams, colloids etc.) are defined on the basis of Pierre-Gilles de Gennes’ definition. At NASA GRC, we are pushing the boundaries for fundamental study of soft matter on Lunar Surface. With regard to Lunar surface science, we are focusing on developing capabilities pertaining to granular materials and bio-soft/active matter to facilitate future efforts in ISRU and bio-ISRU capabilities. In order to achieve fundamental goals of soft matter research within the limitations of Lunar environment, the scientific capabilities need to be small, flexible, modular, off the shelf and the focus needs to be more on developing an interdisciplinary capability that leverages the recent growth in AI/ML and Computer Vision to augment our understanding of fundamental science. This strategy would allow us to reduce our resource requirement during launch, installation, and occupied real estate footprint on Lunar surface In this talk, we will go over 3 different capabilities that we have developed in house and in close collaboration – (a) Differential Dynamic Microscopy (DDM), (b) Portable In-situ Chemical Spectroscopy (PICS) and (c) Computer Vision Enabled Observation. At very high level, Differential Dynamic Microscopy (DDM) allows us to study the structure-property-process relation (microrheology) of bio-soft/active matter using optical microscope and improved image analysis capabilities. PICS uses AI/ML-based advanced signal deconvolution and analysis technique that can work with existing portable spectroscopy tools to perform materials analysis (e.g.- granular materials and bio-soft/active matter) inspection on the go. Finally, computer vision enabled analysis allows us to use simple camera images for 3D reconstruction of experimental process and tracking of objects of interest in an experiment. We expect that this detailed process will allow us reach a thorough understanding of soft matter in Lunar environment. The capabilities developed by us will help to validate and establish fundamental understanding in Lunar environment. This will, in turn, allow us to guide future space exploration missions and expand the knowledge base of the scientific and engineering communities.

Suman Sinha Ray↗
DOE OSTI2025

Targeted genetic manipulation and yeast-like evolutionary genomics in the green alga Auxenochlorella

Auxenochlorella spp. are diploid oleaginous green algae whose streamlined genomes can be readily manipulated by homologous recombination, making them highly amenable to discovery research and bioengineering. Vegetatively diploid organisms experience specific evolutionary phenomena, including allodiploid hybridization, mitotic recombination, loss-of-heterozygosity, and aneuploidy; however, studies of these forces have largely focused on yeasts. Here, we present a telomere-to-telomere phased diploid genome assembly of Auxenochlorella UTEX 250-A (haploid length 22 Mb) and introduce a genetic toolkit for site-specific manipulation of the nuclear genome in multiple strains, featuring several selectable markers, inducible promoters, and fluorescent reporters for protein localization. UTEX 250-A is an allodiploid hybrid of Auxenochlorella protothecoides and Auxenochlorella symbiontica, two species differentiated by extensive chromosomal rearrangements. UTEX 250-A haplotypes are a mosaic of each parental species following mitotic recombination, and two chromosomes are trisomic. Loss-of-heterozygosity events are pervasive across Auxenochlorella and can evolve rapidly in the laboratory. High-quality structural annotation yielded ∼7,500 genes per haplotype. Auxenochlorella have experienced gene family loss and reduction, including core photosynthesis genes, and exhibit periodic adenine and cytosine methylation at promoters and gene bodies, respectively. Approximately 10% of genes, especially those involved in DNA repair and sex, overlap antisense long noncoding RNAs, which may participate in a regulatory mechanism. We demonstrate the utility of Auxenochlorella for fundamental research by knockout of a chlorophyll biosynthesis enzyme, and confirm one trisomy by allele-specific transformation. These results demonstrate the generality of several evolutionary forces associated with vegetative diploidy and provide a foundation for the use of Auxenochlorella as a reference organism.

CHL27↗
DOE OSTI2022

First Measurement of Differential Charged Current Quasielastic-like $\nu_\mu$–Argon Scattering Cross Sections In Kinematic Imbalance Variables With The MicroBooNE Detector

We report the first measurement of flux-integrated multi-differential cross sections for charged-current events with muon neutrinos scattering on argon with solely a muon and a single proton in the final state as a function of kinematic imbalance variables. The measurement was carried out using the Booster Neutrino Beam at Fermi National Accelerator Laboratory within the MicroBooNE Liquid Argon Time Projection Chamber detector with an exposure of 6.79 × 10 20 protons on target. Events were selected to enhance the contribution of charged-current mesonless interactions with one proton detected in the final state. The data discussed here are reported in terms of multidifferential cross sections in kinematic imbalance variables, which are generally sensitive to nuclear effects. The double-differential results in these variables can provide an excellent handle to disentagle specific nuclear aspects not easily isolated via single differential cross sections. Our results pave a path towards identifying regions of the phase-space where future interaction modeling development and Monte Carlo neutrino generator tuning efforts should concentrate. EVENT SELECTION Neutrino oscillation measurements aim to extract neutrino mixing angles, mass differences, the value of the chargeparity violating phase in the lepton sector, and to search for new physics beyond the Standard Model [1, 2]. For that to be achieved, an unprecedented understanding of neutrino-argon interactions is of utmost importance since a growing number of neutrino oscillation experiments employ Liquid Argon Time Projector Chamber (LArTPC) neutrino detectors [3–6]. The accuracy to which these experiments can extract neutrino oscillation parameters requires a good understanding of the neutrino energy. Experimentally, this energy is deduced from the measured kinetic energies of particles that are emitted following the neutrino interaction in the detector. The kinematic properties of such finalstate particles reflect complex dynamics due to nuclear and initial-state effects of the interaction [7]. However, certain categories of nuclear effects can be isolated by variables built specifically to characterize the degeneracy between such effects [8–10]. This note reports cross sections in kinematic variables sensitive to nuclear effects using events with one detected muon with momentum 0.1 < pµ < 1.2 GeV/c, and exactly one proton with 0.3 < pp < 1 GeV/c. This signal definition includes events with any number of protons below 300 MeV/c, neutrons at any momenta, and charged pions with momentum lower than 70 MeV/c. This choice is guided by the fact that their experimental signature of correlated muon-proton pairs is fairly straightforward to reconstruct [11–22]. Such events primarily originate from chargedcurrent (CC) neutrino-nucleon quasielastic (QE) scattering interactions where the neutrino removes a single intact nucleon from the nucleus without producing any additional particles. This definition can also include contributions from interactions that lead to the production of additional particles that are absent from the final state due to nuclear effects, such as pion absorption, or have momenta that are below the experimental detection threshold.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗
NASA NTRS2000

High-Speed Research Surveillance Symbology Assessment Experiment

Ten pilots flew multiple approach and departure scenarios in a simulation experiment of the High-Speed Civil Transport to evaluate the utility of different airborne surveillance display concepts. The primary eXternal Visibility System (XVS) display and the Navigation Display (ND) were used to present tactical and strategic surveillance information, respectively, to the pilot. Three sensors, the Traffic Alert and Collision Avoidance System, radar, and the Automatic Dependent Surveillance-Broadcast system, were modeled for this simulation and the sensors surveillance information was presented in two different symbology sets to the pilot. One surveillance symbology set used unique symbol shapes to differentiate among the sensors, while the other set used common symbol shapes for the sensors. Surveillance information in the form of escape guidance from threatening traffic was also presented to the pilots. The surveillance information (sensors and escape guidance) was either presented head-up on the primary XVS display and head-down on the ND or head-down on the ND only. Both objective and subjective results demonstrated that the display concepts having surveillance information presented head-up and head-down have surveillance performance benefits over those concepts having surveillance information displayed head-down only. No significant symbology set differences were found for surveillance task performance.

Kramer, Lynda J.↗
NASA NTRS2003

Wind Tunnel Database Development using Modern Experiment Design and Multivariate Orthogonal Functions

A wind tunnel experiment for characterizing the aerodynamic and propulsion forces and moments acting on a research model airplane is described. The model airplane called the Free-flying Airplane for Sub-scale Experimental Research (FASER), is a modified off-the-shelf radio-controlled model airplane, with 7 ft wingspan, a tractor propeller driven by an electric motor, and aerobatic capability. FASER was tested in the NASA Langley 12-foot Low-Speed Wind Tunnel, using a combination of traditional sweeps and modern experiment design. Power level was included as an independent variable in the wind tunnel test, to allow characterization of power effects on aerodynamic forces and moments. A modeling technique that employs multivariate orthogonal functions was used to develop accurate analytic models for the aerodynamic and propulsion force and moment coefficient dependencies from the wind tunnel data. Efficient methods for generating orthogonal modeling functions, expanding the orthogonal modeling functions in terms of ordinary polynomial functions, and analytical orthogonal blocking were developed and discussed. The resulting models comprise a set of smooth, differentiable functions for the non-dimensional aerodynamic force and moment coefficients in terms of ordinary polynomials in the independent variables, suitable for nonlinear aircraft simulation.

Morelli, Eugene A.↗
DOE OSTI2024

Temperature-dependent mechanical properties and crystal plasticity parameters for additively manufactured Haynes-214 alloy: Experiments and numerical modeling

Our experimental mechanical testing data demonstrated that the additively manufactured (AM) laser powder bed fusion (L-PBF) Haynes-214 alloy exhibits non-linear mechanical properties as the temperature rises from ambient to 870 °C. Crystal plasticity (CP) simulations provide an effective approach to gaining deeper insights into microstructure-property linkages under thermomechanical loading. This method can reduce the need for costly high-temperature mechanical testing while accounting for the effects of crystallographic texture and grain morphology on the mechanical behavior of AM materials. However, calibrating a CP model is time-consuming because individual simulations are computationally expensive and hundreds (or more) of iterations over parameter sets may be required. To address this issue, we have designed a machine learning-differential evolution (ML-DE) CP framework that can accurately interpolate the tensile properties of AM L-PBF Haynes-214 alloy across a wide temperature range from ambient to 870 °C, with minimal reliance on experimental data. The framework uses electron backscatter diffraction (EBSD) measurements to generate statistically equivalent microstructural volume elements to serve as inputs to the CP modeling framework. Stress–strain curves were generated from 1000 CP simulations, which serve as the training data set for the three ML regression algorithms explored: linear, extra-trees, and multi-layer perceptron. These three regression models were independently evaluated to compare their efficiency and identify the most suitable algorithm for the given problem. Results revealed that the extra-trees ML regressor outperforms the other models in both qualitative and quantitative aspects with an R 2 of 0.98. Subsequently, the differential evolution optimization approach is employed to calibrate the ML-based CP material parameters with experimental results obtained at various temperatures. Finally, temperature-dependent CP material parameters are formulated. The effectiveness and efficiency of the designed framework are validated through comparison with experimental results, demonstrating a high degree of agreement. These calibrated parametric constitutive equations enable further use of the CP model to study the deformation behavior of this alloy under a wide range of thermo-mechanical loading conditions.

36 MATERIALS SCIENCE↗
NASA NTRSDate not supplied

Beyond Low-Earth Orbit: Characterizing Immune and microRNA Differentials Following Simulated Deep Spaceflight Conditions in Mice

Spaceflight missions can cause immune system dysfunction in astronauts with little understanding of immune outcomes in deep space. This study assessed immune responses in mice following ground-based, simulated deep spaceflight conditions, compared to data from astronauts on ISS missions. For ground studies, we simulated microgravity using the hindlimb unloaded mouse model alone or in combination with acute simulated galactic cosmic rays or solar particle events irradiation. Immune profiling results revealed unique immune diversity following each experimental condition, suggesting each stressor results in distinct circulating immune responses, with clear consequences for deep spaceflight. Circulating plasma microRNA sequence analysis revealed involvement in immune system dysregulation. Furthermore, a large astronaut cohort showed elevated inflammation during LEO missions, thereby supporting our simulated ground experiments in mice. Herein, circulating immune biomarkers are defined by distinct deep space irradiation types coupled to simulated microgravity and could be targets for future space health initiatives.

deep spaceflight stressors↗
DOE OSTI2019

Collapse of Reacted Fracture Surface Decreases Permeability and Frictional Strength

Abstract Geochemical and geomechanical perturbations of the subsurface caused by the injection of fluids present risks of leakage and seismicity. This study investigated how acidic fluid flow affects hydraulic and frictional properties of fractures using experiments with 3.8‐cm‐long specimens of Eagle Ford shale, a laminated shale with carbonate‐rich strata. In low‐pressure flow cells, one set of samples was exposed to acidic brine and another set was exposed to neutral brine. X‐ray computed tomography and energy‐dispersive X‐ray spectroscopy revealed that samples exposed to acidic brine were calcite‐depleted and had developed a porous altered layer, while the other set showed no evidence of alteration. After reaction, samples were compressed and sheared in a triaxial cell that supplied normal stress and differential pore pressure at prescribed sliding velocities, independently measuring friction and permeability. During the initial compression, the porous altered layer collapsed into fine particles that filled the fracture. This effectively impeded flow and sealed the fracture, resulting in fracture permeability to decrease 1 to 2 orders of magnitude relative to the unaltered fractures. This is a favorable outcome in subsurface applications where the goal is to reduce leakage risks. However, during shear the reacted fracture had lower frictional strength because the fine‐grained particles in the collapsed layer prevented the formation of interlocking microasperities. Therefore, coupled geochemical and geomechanical processes that could favorably seal fractures could also increase the likelihood of induced seismicity. These findings have important implications for geological carbon sequestration, pressurized fluid energy storage, geothermal energy, and other subsurface technologies.

58 GEOSCIENCES↗
DOE OSTI2025

Does class matter? Understanding differential pandemic recovery via a building typology

This study investigates the recovery of building-level footfall from the COVID-19 pandemic using privacy-preserving mobile devices-based footfall data within 60 downtown areas in the USA and Canada. Using clustering, we identify five distinct building typologies based on their characteristics, including rent, quality and recovery rates. The results reveal significant variation of recovery rates by building features. We find negative relationships with footfall recovery for both the percentage of office and remote work tenants and building quality. In contrast, buildings with traditional work tenants and retail functions achieve higher recovery rates. We also test the ‘flight to quality’ hypothesis via on our typology results. High-quality office buildings (Class A+) continue to have high rents but experience low physical footfall recovery, which suggests that this class is not as resilient as portrayed. The findings thus suggest the importance of considering both economic and footfall resilience in evaluating the performance of office buildings.

Covid-19↗
NASA NTRS1973

Precision pointing thrustor.

A satellite experiment to test the predicted relativistic precession of a gyroscope moving through a gravitational field has been under development at Stanford University for a number of years. The instruments will be located in a liquid helium bath to insure dimensional stability and to permit using superconducting types of circuitry for readout of the gyro orientation. Heat leaks in the system cause the helium to boil and the resultant helium gas is used for attitude control. The principal subject of the paper is the design and experimental evaluation of an electromagnetically actuated differential thrustor which was built and tested at Stanford University. The results are unique because most propulsion systems operate on-off in order to utilize propellant efficiently. In this case, the gas must flow continually to provide cooling, and the requirements are primarily for low power, small volume, and high reliability.

Bull, J. S.↗
NASA NTRS1981

Analysis of Barkhausen noise to assess shrink fit stresses

The possible application of Barkhausen Noise Analysis to assess shrink fit stresses in steel bushings was investigated. Ten specimens of four different size NAS steel bushings were used in experiments to determine the relationship between the Barkhausen signal amplitude and the hoop-stress in the bushings. This relationship was investigated for specimens which were loaded by a simple clamping fixture and specimens subjected to actual thermal interference fits. The results show that while the relationship of Barkhausen signal amplitude to hoop stress is predictable for specimens loaded by the simple clamping fixture, the relationship was less predictable for actual thermal fit bushings. The variation in results could possibly be due to variable levels of axial stress produced by the differential thermal expansion of the steel and aluminum.

Nondestructive testing↗
NASA NTRS1993

Mass balance assessment using GPS

Mass balance is an integral part of any comprehensive glaciological investigation. Unfortunately, it is hard to determine at remote locations where there is no fixed reference. The Global Positioning System (GPS) offers a solution. Simultaneous GPS observations at a known location and the remote field site, processed differentially, will accurately position the camp site. From there, a monument planted in the firn atop the ice can also be accurately positioned. Change in the monument's vertical position is a direct indicator of ice thickness change. Because the monument is not connected to the ice, its motion is due to both mass balance change and to the settling of firn as it densifies into ice. Observations of relative position change between the monument and anchors at various depths within the firn are used to remove the settling effect. An experiment to test this method has begun at Byrd Station on the West Antarctic Ice Sheet and the first epoch of observations was made. Analysis indicates that positioning errors will be very small. It appears likely that the largest errors involved with this technique will arise from ancillary data needed to determine firn settling.

Hulbe, Christina L.↗
NASA NTRS1994

Multiparameter radar study of rainfall: Potential application to area-time integral studies

Multiparameter radars measure one or more additional parameters in addition to the coventional reflectivity factor. The combination of radar observations from a multiparameter radar is used to study the time evolution of rainstorms. A technique is presented to self-consistently compare the area-time integral (ATI) and rainfall volume estimates from convective storms, using two different measurements from a multiparameter radar. Rainfall volumes for the lifetime of individual storms are computed using the reflectivity at S band (10-cm wavelength) as well as one-way specific attenuation at X band (3-cm wavelength). Area-time integrals are computed by summing all areas in each radar snapshot having reflectivities (S band) in excess of a preselected threshold. The multiparameter radar data used in this study were acquired by the National Center for Atmospheric Research (NCAR) CP-2 radar during the Cooperative Huntsville Meteorological Experiment (COHMEX) and the Convection and Precipitation/Electrification Experiment (CaPE), respectively. ATI studies were accomplished in this work using multiparameter radar data acquired during the lifetime of six convective events that occurred in the COHMEX radar coverage area. A case study from the COMHEX field campaign (20 July 1986) was selected to depict the various stages in the evolution of a storm over which the ATI and rainfall volume computations were performed using multiparameter radar data. Another case study from the CaPE field campaign (12 August 1991) was used to demonstrate the evolution of a convective cell based on differential reflectivity observations.

Raghavan, R.↗
NASA NTRS2008

Mice Drawer System

The Mice Drawer System (MDS) is an Italian Space Agency (ASI) facility which is able to support mice onboard the International Space Station during long-duration exploration missions (from 100 to 150-days) by living space, food, water, ventilation and lighting. Mice can be accommodated either individually (maximum 6) or in groups (4 pairs). MDS is integrated in the Space Shuttle middeck during transportation (uploading and downloading) to the ISS and in an EXPRESS Rack in Destiny, the US Laboratory during experiment execution. Osteoporosis is a debilitating disease that afflicts millions of people worldwide. One of the physiological changes experienced by astronauts during space flight is the accelerated loss of bone mass due to the lack of gravitational loading on the skeleton. This bone loss experienced by astronauts is similar to osteoporosis in the elderly population. MDS will help investigate the effects of unloading on transgenic (foreign gene that has been inserted into its genome to exhibit a particular trait) mice with the Osteoblast Stimulating Factor-1, OSF-1, a growth and differentiation factor, and to study the genetic mechanisms underlying the bone mass pathophysiology. MDS will test the hypothesis that mice with an increased bone density are likely to be more protected from osteoporosis, when the increased bone mass is a direct effect of a gene involved in skeletogenesis (skeleton formation). Osteoporosis is a debilitating disease that afflicts millions worldwide. One of the physiological changes experienced by astronauts during space flight is the accelerated loss of bone mass due to the lack of gravitational loading on the skeleton, a loss that is similar to osteoporosis in the elderly population on Earth. Osteoblast Stimulating Factor-1 (OSF-1), also known as pleiotrophin (PTN) or Heparin-Binding Growth- Associated Molecule (HB-GAM) belongs to a family of secreted heparin binding proteins..OSF-1 is an extracellular matrix-associated growth and differentiation factor that is normally expressed in cartilage; it can stimulate the proliferation and differentiation of human osteoprogenitor cells (cell that differentiate into an osteoblast) in vitro. The Mice Drawer System will study the effects of microgravity on transgenic mouse bones in order to identify genetic mechanisms playing a role in the reduction of the bone mass observed in humans and animals as a consequence of long-duration (greater than 100 days) microgravity exposure. Onboard the ISS, MDS is relatively self-sufficient; a crewmember will check the health status of the rodents on a daily basis, by assessing them through the viewing window. Water levels will be assessed by the crew daily and refilled as needed. Replacement of the food bars and replacement of the waste filters will be conducted inflight by crewmembers every 20-days.

Cancedda, Ranieri↗
DOE OSTI2023

A unified hp-HDG framework for Friedrichs' PDE systems

Here, this work proposes a unified hp-adaptivity framework for hybridized discontinuous Galerkin (HDG) method for a large class of partial differential equations (PDEs) of Friedrichs' type. In particular, we present unified hp-HDG formulations for abstract one-field and two-field structures and prove their well-posedness. In order to handle non-conforming interfaces we simply take advantage of HDG built-in mortar structures. With split-type mortars and the approximation space of trace, a numerical flux can be derived via Godunov approach and be naturally employed without any additional treatment. As a consequence, the proposed formulations are parameter-free. We perform several numerical experiments for time-independent and linear PDEs including elliptic, hyperbolic, and mixed-type to verify the proposed unified hp-formulations and demonstrate the effectiveness of hp-adaptation. Two adaptivity criteria are considered: one is based on a simple and fast error indicator, while the other is rigorous but more expensive using an adjoint-based error estimate. The numerical results show that these two approaches are comparable in terms of convergence rate even for problems with strong gradients, discontinuities, and singularities.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2020

Multi-Temporal Predictive Modelling of Sorghum Biomass Using UAV-Based Hyperspectral and LiDAR Data

High-throughput phenotyping using high spatial, spectral, and temporal resolution remote sensing (RS) data has become a critical part of the plant breeding chain focused on reducing the time and cost of the selection process for the “best” genotypes with respect to the trait(s) of interest. In this paper, the potential of accurate and reliable sorghum biomass prediction using visible and near infrared (VNIR) and short-wave infrared (SWIR) hyperspectral data as well as light detection and ranging (LiDAR) data acquired by sensors mounted on UAV platforms is investigated. Predictive models are developed using classical regression-based machine learning methods for nine experiments conducted during the 2017 and 2018 growing seasons at the Agronomy Center for Research and Education (ACRE) at Purdue University, Indiana, USA. The impact of the regression method, data source, timing of RS and field-based biomass reference data acquisition, and the number of samples on the prediction results are investigated. R2 values for end-of-season biomass ranged from 0.64 to 0.89 for different experiments when features from all the data sources were included. Geometry-based features derived from the LiDAR point cloud to characterize plant structure and chemistry-based features extracted from hyperspectral data provided the most accurate predictions. Evaluation of the impact of the time of data acquisition during the growing season on the prediction results indicated that although the most accurate and reliable predictions of final biomass were achieved using remotely sensed data from mid-season to end-of-season, predictions in mid-season provided adequate results to differentiate between promising varieties for selection. The analysis of variance (ANOVA) of the accuracies of the predictive models showed that both the data source and regression method are important factors for a reliable prediction; however, the data source was more important with 69% significance, versus 28% significance for the regression method.

09 BIOMASS FUELS↗
NASA NTRS1985

Phase averaged transverse vorticity measurements in an excited, two-dimensional mixing layer

Experiments were run to characterize the global vorticity distribution in an excited plane mixing layer. A reciprocating piston excited the mixing layer at a 0.0053 intensity, a Strouhal number of 0.97, and a 15 Hz frequency. An X-wire anemometer and a pitot tube furnished data in the 13 m/sec free stream velocity flow. Deep depressions were observed in the velocity contours on the high-speed side of the mixing layer, while primary vortex growth occurred on the low-speed side. The cores of the vortices moved at highly differentiated velocities. Phase plots were also generated to show tearing and fusing of the vortex contours.

Disimile, P. J.↗