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At least 415 records · Page 23

Use of system identification techniques for improving airframe finite element models using test data

A method for using system identification techniques to improve airframe finite element models using test data has been developed and demonstrated. The method uses linear sensitivity matrices to relate changes in selected physical parameters to changes in the total system matrices. The values for these physical parameters were determined using constrained optimization with singular value decomposition. The method was confirmed using both simple and complex finite element models for which pseudo-experimental data was synthesized directly from the finite element model. The method was then applied to a real airframe model which incorporated all of the complexities and details of a large finite element model and for which extensive test data was available. The method was shown to work, and the differences between the identified model and the measured results were considered satisfactory.

Hanagud, Sathya V.↗

Use of system identification techniques for improving airframe finite element models using test data

A method for using system identification techniques to improve airframe finite element models using test data was developed and demonstrated. The method uses linear sensitivity matrices to relate changes in selected physical parameters to changes in the total system matrices. The values for these physical parameters were determined using constrained optimization with singular value decomposition. The method was confirmed using both simple and complex finite element models for which pseudo-experimental data was synthesized directly from the finite element model. The method was then applied to a real airframe model which incorporated all of the complexities and details of a large finite element model and for which extensive test data was available. The method was shown to work, and the differences between the identified model and the measured results were considered satisfactory.

Hanagud, Sathya V.↗

Survey of Aerothermodynamics Facilities Useful for the Design of Hypersonic Vehicles Using Air-Breathing Propulsion

This paper surveys the use of aerothermodynamic facilities which have been useful in the study of external flows and propulsion aspects of hypersonic, air-breathing vehicles. While the paper is not a survey of all facilities, it covers the utility of shock tunnels and conventional hypersonic blow-down facilities which have been used for hypersonic air-breather studies. The problems confronting researchers in the field of aerothermodynamics are outlined. Results from the T5 GALCIT tunnel for the shock-on lip problem are outlined. Experiments on combustors and short expansion nozzles using the semi-free jet method have been conducted in large shock tunnels. An example which employed the NASA Ames 16-Inch shock tunnel is outlined, and the philosophy of the test technique is described. Conventional blow-down hypersonic wind tunnels are quite useful in hypersonic air-breathing studies. Results from an expansion ramp experiment, simulating the nozzle on a hypersonic air-breather from the NASA Ames 3.5 Foot Hypersonic wind tunnel are summarized. Similar work on expansion nozzles conducted in the NASA Langley hypersonic wind tunnel complex is cited. Free-jet air-frame propulsion integration and configuration stability experiments conducted at Langley in the hypersonic wind tunnel complex on a small generic model are also summarized.

Arnold, James O.↗

Using Leaf Chlorophyll to Parameterize Light-Use-Efficiency Within a Thermal-Based Carbon, Water and Energy Exchange Model

Chlorophylls absorb photosynthetically active radiation and thus function as vital pigments for photosynthesis, which makes leaf chlorophyll content (C(sub ab) useful for monitoring vegetation productivity and an important indicator of the overall plant physiological condition. This study investigates the utility of integrating remotely sensed estimates of C(sub ab) into a thermal-based Two-Source Energy Balance (TSEB) model that estimates land-surface CO2 and energy fluxes using an analytical, light-use-efficiency (LUE) based model of canopy resistance. The LUE model component computes canopy-scale carbon assimilation and transpiration fluxes and incorporates LUE modifications from a nominal (species-dependent) value (LUE(sub n)) in response to short term variations in environmental conditions, However LUE(sub n) may need adjustment on a daily timescale to accommodate changes in plant phenology, physiological condition and nutrient status. Day to day variations in LUE(sub n) were assessed for a heterogeneous corn crop field in Maryland, U,S.A. through model calibration with eddy covariance CO2 flux tower observations. The optimized daily LUE(sub n) values were then compared to estimates of C(sub ab) integrated from gridded maps of chlorophyll content weighted over the tower flux source area. The time continuous maps of daily C(sub ab) over the study field were generated by focusing in-situ measurements with retrievals generated with an integrated radiative transfer modeling tool (accurate to within +/-10%) using at-sensor radiances in green, red and near-infrared wavelengths acquired with an aircraft imaging system. The resultant daily changes in C(sub ab) within the tower flux source area generally correlated well with corresponding changes in daily calibrated LUE(sub n) derived from the tower flux data, and hourly water, energy and carbon flux estimation accuracies from TSEB were significantly improved when using C(sub ab) for delineating spatio-temporal variations in LUE(sub n). The results demonstrate the synergy between thermal infrared and shortwave reflective wavebands in producing valuable remote sensing data for operational monitoring of carbon and water fluxes.

Houlborg, Rasmus↗

Use of Land Use Land Cover Change Mapping Products in Aiding Coastal Habitat Conservation and Restoration Efforts of the Mobile Bay NEP

The Mobile Bay region has undergone significant land use land cover change (LULC) over the last 35 years, much of which is associated with urbanization. These changes have impacted the region s water quality and wildlife habitat availability. In addition, much of the region is low-lying and close to the Gulf, which makes the region vulnerable to hurricanes, climate change (e.g., sea level rise), and sometimes man-made disasters such as the Deepwater Horizon (DWH) oil spill. Land use land cover change information is needed to help coastal zone managers and planners to understand and mitigate the impacts of environmental change on the region. This presentation discusses selective results of a current NASA-funded project in which Landsat data over a 34-year period (1974-2008) is used to produce, validate, refine, and apply land use land cover change products to aid coastal habitat conservation and restoration needs of the Mobile Bay National Estuary Program (MB NEP). The project employed a user defined classification scheme to compute LULC change mapping products for the entire region, which includes the majority of Mobile and Baldwin counties. Additional LULC change products have been computed for select coastal HUC-12 sub-watersheds adjacent to either Mobile Bay or the Gulf of Mexico, as part of the MB NEP watershed profile assessments. This presentation will include results of additional analyses of LULC change for sub-watersheds that are currently high priority areas, as defined by MB NEP. Such priority sub-watersheds include those that are vulnerable to impacts from the DWH oil spill, as well as sub-watersheds undergoing urbanization. Results demonstrating the nature and permanence of LULC change trends for these higher priority sub-watersheds and results characterizing change for the entire 34-year period and at approximate 10-year intervals across this period will also be presented. Future work will include development of value-added coastal habitat quality assessment products that will be used by the MB NEP and its partners in the planning of coastal conservation and restoration activities.

Spruce, Joseph P.↗

Use of DSC and DMA Techniques to Help Investigate a Material Anomaly for PTFE Used in Processing a Piston Cup for the Urine Processor Assembly (UPA) on International Space Station (ISS)

Human urine and flush water are eventually converted into drinking water with the Urine Processor Assembly (UPA) aboard the International Space Station (ISS). This conversion is made possible through the Distillation Assembly (DA) of the UPA. One component of the DA is a molded circular piston cup made of virgin polytetrafluoroethylene (PTFE). The piston cup is assembled to a titanium component using eight fasteners and washers. Molded PTFE produced for spare piston cups in the first quarter of 2010 was different in appearance and texture, and softer than material molded for previous cups. For the suspect newer PTFE material, cup fasteners were tightened to only one-half the required torque value, yet the washers embedded almost halfway into the material. The molded PTFE used in the DA piston cup should be Type II, based on AMS 3667D and ASTM D4894 specifications. The properties of molded PTFE are considerably different between Type I and II materials. Engineers working with the DA thought that if Type I PTFE was molded by mistake instead of Type II material, that could have resulted in the anomalous material properties. Typically, the vendor molds flat sheet PTFE from the same material lot used to mold the piston cups, and tensile testing as part of quality control should verify that the PTFE is Type II material. However, for this discrepant lot of material, such tensile data was not available. Differential scanning calorimetry (DSC) and dynamic mechanical analysis (DMA) were two of the testing techniques used at the NASA/Marshall Space Flight Center (MSFC) to investigate the anomaly for the PTFE material. Other techniques used on PTFE specimens were: Shore D hardness testing, tensile testing on dog bone specimens and a qualitative estimation of porosity by optical and scanning electron microscopy.

Wingard, Doug↗

Development of thermostable carbonic anhydrases using structure-guided recombination for use in CO2 removal systems on spacecraft

Carbon capture and storage has been a research area of great interest in recent years asa method for mitigation of CO2emissions, due to the effects of climate change. The development of technologies for the efficient capture of CO2are also of great interest for human spaceflight applications. One of the most promising technologies in this area is CO2 scrubbing using liquid amines, unfortunately, liquid amines with low heats of desorption tend to have slow CO2binding kinetics. One potential solution to this problem is to use the enzyme carbonic anhydrase (CA) to enhance the kinetics of CO2binding to liquid amines, allowing the overall process to be more energy efficient. Interest in using carbonic anhydrase as a biocatalyst has led to a number of efforts to improve the thermostability and solvent tolerance of several distinct carbonic anhydrase enzymes. In the work described here, we screened through a diverse set of natural carbonic anhydrases to identify candidates for protein engineering aimed at increased stability and activity in various liquid amines. We then used SCHEMA structure-guided recombination to develop a set of chimeric carbonic anhydrases with high thermostability and activity. These chimeras were used as the starting points for further protein engineering work targeting activity in liquid amine systems. Our ultimate goal is to test the engineered enzymes in a liquid amine system for cabin air revitalization on ISS or other spacecraft.

Life Support↗

Development of Thermostable Carbonic Anhydrases Using Structure-Guided Recombination for Use in CO2 Removal Systems on Spacecraft

Carbon capture and storage has been a research area of great interest in recent years as a method for mitigation of CO2 emissions, due to the effects of climate change. The development of technologies for the efficient capture of CO2 are also of great interest for human spaceflight applications. One of the most promising technologies in this area is CO2 scrubbing using liquid amines, unfortunately, liquid amines with low heats of desorption tend to have slow CO2 binding kinetics. One potential solution to this problem is to use the enzyme carbonic anhydrase (CA) to enhance the kinetics of CO2 binding to liquid amines, allowing the overall process to be more energy efficient. Interest in using carbonic anhydrase as a biocatalyst has led to a number of efforts to improve the thermostability and solvent tolerance of several distinct carbonic anhydrase enzymes. In the work described here, we screened through a diverse set of natural carbonic anhydrases to identify candidates for protein engineering aimed at increased stability and activity in various liquid amines. We then used SCHEMA structure-guided recombination to develop a set of chimeric carbonic anhydrases with high thermostability and activity. These chimeras were used as the starting points for further protein engineering work targeting activity in liquid amine systems. Our ultimate goal is to test the engineered enzymes in a liquid amine system for cabin air revitalization on ISS or other spacecraft.

Life Support, Carbon dioxide, Carbonic anhydrase, ↗

Assessing the use of UAS-related terms in ASRS using Seed Topic Modeling

Context: The NASA Aviation Safety Reporting System (ASRS) is a voluntary confidential aviation safety reporting system. The ASRS receives reports from pilots, air traffic controllers, flight attendants and other involved in aviation operations. The reports are de-identified and coded by ASRS expert safety analysts. The de-identified reports are then disseminated to the aviation community in a number of ways including entry into an online database. Augmenting the discovery of topics of user interest in this online database would therefore be beneficial to the community it serves. Aim: We propose and execute an experiment to assess the use of seed term topic modeling using the database narratives to identify UAS reports. The use of seed term topic modeling would enable users to identify groups of related narratives associated to a topic of their interest. Method: We use a newly curated field in ASRS reports which identify UAS from non-UAS reports in combination of different set of UAS related terms to assess if seed topic modeling can be used in ASRS.

LDA↗

Modeling urban building energy use: A review of modeling approaches and procedures

With rapid urbanization and economic development, the world has been experiencing an unprecedented increase in energy consumption and greenhouse gas (GHG) emissions. While reducing energy consumption and GHG emissions is a common interest shared by major developed and developing countries, actions to enable these global reductions are generally implemented at the city scale. This is because baseline information from individual cities plays an important role in identifying economical options for improving building energy efficiency and reducing GHG emissions. Numerous approaches have been proposed for modeling urban building energy use in the past decades. This paper aims to provide an up-to-date review of the broad categories of energy models for urban buildings and describes the basic workflow of physics-based, bottom-up models and their applications in simulating urban-scale building energy use. Because there are significant differences across models with varied potential for application, strengths and weaknesses of the reviewed models are also presented. This is followed by a discussion of challenging issues associated with model preparation and calibration.

Bottom-up approaches↗

Manipulative experiments demonstrate how long-term soil moisture changes alter controls of plant water use

Tree transpiration depends on biotic and abiotic factors that might change in the future, including precipitation and soil moisture status. Although short-term sap flux responses to soil moisture and evaporative demand have been the subject of attention before, the relative sensitivity of sap flux to these two factors under long-term changes in soil moisture conditions has rarely been determined experimentally. We tested how long-term artificial change in soil moisture affects the sensitivity of tree-level sap flux to daily atmospheric vapor pressure deficit (VPD) and soil moisture variations, and the generality of these effects across forest types and environments using four manipulative sites in mature forests. Exposure to relatively long-term (two to six years) soil moisture reduction decreases tree sap flux sensitivity to daily VPD and relative extractable water (REW) variations, leading to lower sap flux even under high soil moisture and optimal VPD. Inversely, trees subjected to long-term irrigation showed a significant increase in their sensitivity to daily VPD and REW, but only at the most water-limited site. The ratio between the relative change in soil moisture manipulation and the relative change in sap flux sensitivity to VPD and REW variations was similar across sites suggesting common adjustment mechanisms to long-term soil moisture status across environments for evergreen tree species. Overall, our results show that long-term changes in soil water availability, and subsequent adjustments to these novel conditions, could play a critical and increasingly important role in controlling forest water use in the future.

acclimation↗

Deep Direct-Use Feasibility Study Numerical Modeling and Uncertainty Analysis using iTOUGH2 for West Virginia University

To reduce the geothermal exploration risk, a feasibility study is performed for a deep direct-use system proposed at the West Virginia University (WVU) Morgantown campus. This study applies numerical simulations to investigate reservoir impedance and thermal production. Because of the great depth of the geothermal reservoir, few data are available to characterize reservoir features and properties. As a result, the study focuses on the following three aspects: 1. model choice for predicting reservoir impedance and thermal breakthrough: after investigating three potential models (one single permeability model and two dual permeability models) for flow through fractured rock, it is decided to use single permeability model for further analysis; 2. well placement (horizontal vs. vertical) options: horizontal well placement seems to be more robust to heterogeneity and the impedance is more acceptable; 3. Prediction uncertainty: the most influential parameters are identified using a First-Order-Second-Moment uncertainty propagation analysis, and the uncertain range of the model predictions is estimated by performing a Monte Carlo simulation. Heterogeneity has a large impact on the perdition, therefore, is considered in the predictive model and uncertainty analysis. The numerical model results and uncertainty analysis are used for economic analysis. The dataset submitted here support the described study. Manuscript is submitted to Geothermics, will be linked once paper is accepted.

15 GEOTHERMAL ENERGY↗

Remaining Useful Strength (RUS) Prediction of SiCf-SiCm Composite Materials Using Deep Learning and Acoustic Emission

Prognosis techniques for prediction of remaining useful life (RUL) are of crucial importance to the management of complex systems for they can lead to appropriate maintenance interventions and improvements in reliability. While various data-driven methods have been introduced to predict the remaining useful life (RUL) of machinery systems or batteries, no research has been reported on the remaining useful strength (RUS) prediction of silicon carbide fiber reinforced silicon carbide matrix (SiCf-SiCm) materials with pivotal role in its potential usage as a structural material in nuclear reactors and turbine engines. Knowledge of its degradation process is of the utmost importance to the manufacturers. For this purpose, two approaches based on the machine-learning techniques of random-forest (RF) and convolutional neural network (CNN) are proposed to predict the RUS of SiCf-SiCm using only acoustic emission (AE) signals generated during the material’s stress applying process. Experimental results show that the CNN models achieved better predictive performance than the RF models but the latter with expert-engineered features achieves better prediction for AE signals in the early stage of degradation. Additionally, our results demonstrate that both models can correctly predict the SiCf-SiCm RUS as evaluated by our robust testing method from which the best average root mean square error (RMSE) and Pearson correlation coefficient of 3.55 ksi units and 0.85 were obtained.

36 MATERIALS SCIENCE↗

Intensity and daily pattern of passenger vehicle use by region and class in China: estimation and implications for energy use and electrification

Given the explosive growth of the passenger vehicle market and energy demands in China, research on vehicle-use intensity and driver-travel patterns is critical for better assessing travel demand and its implications for alternative fuel vehicles, energy security, and environmental policies. This study attempts to estimate annual vehicle kilometers traveled (AVKT) per privately-owned passenger vehicle and their daily distance patterns by vehicle class and geographic region. The data sample from a survey consists of 169,292 privately owned passenger vehicles, made by 177 car manufacturers during 2003–2018, running in 82 cities from 27 provincial regions. The log-transformed average AVKT is estimated to be 12,377 km with 95% probability ranging from 5490 to 28,579 km. The investigation reveals that vehicles from South China have the highest AVKT at 13,320 km. Generally, vehicles in small cities have higher AVKT than in big cities, except AVKT of tier 1 cities being higher. Another trend is that more expensive or larger vehicles tend to be driven more. A model is fitted for estimating AVKT based on region, city type, automaker, price range, and certain vehicle features including class and age. Data of daily commuting distances in recent years are also analyzed. The average daily commuting distances typically range from 21 to 28 km. Using the validated Gamma distribution method, daily distance distributions are specified for different regions. It is found that 99% of the daily driving distance is no more than 88.0–112.0 km, depending on region. Utility factors of plug-in electric vehicles are also estimated to be much higher than those based on driving data in the USA. Finally, these findings suggest global mitigations strategies on vehicle fuel use, electrification, and greenhouse gases should consider vehicle-use intensity at the regional level.

33 ADVANCED PROPULSION SYSTEMS↗

Increased influence of nitrogen limitation on CO 2 emissions from future land use and land use change

Abstract In the latest projections of future greenhouse gas emissions for the Intergovernmental Panel on Climate Change (IPCC), few Earth System Models included the effect of nitrogen limitation, a key process limiting forest regrowth. Few included forest management (wood harvest). We estimate the impacts of nitrogen limitation on the CO 2 emissions from land use and land use change (LULUC), including wood harvest, for the period 1900–2100. We use a land surface model that includes a fully coupled carbon and nitrogen cycle and accounts for forest regrowth processes following agricultural abandonment and wood harvest. Future projections are based on the four Representation Concentration Pathways used in the IPCC Fifth Assessment Report, and we account for uncertainty in future climate for each scenario based on ensembles of climate model outputs. Results show that excluding nitrogen limitation will underestimate global LULUC emissions by 34–52 PgC (20–30%) during the 20th century (range across three different historical LULUC reconstructions) and by 128–187 PgC (90–150%) during the 21st century (range across the four IPCC scenarios). The full range for estimated LULUC emissions during the 21st century including climate model uncertainty is 91 to 227 PgC (with nitrogen limitation included). The underestimation increases with time because (1) projected annual wood harvest rates from forests summed over the 21st century are 380–1080% higher compared to those of the 20th century, resulting in more regrowing secondary forests; (2) nitrogen limitation reduces the CO 2 fertilization effect on net primary production of regrowing secondary forests following wood harvest and agricultural abandonment; and (3) nitrogen limitation effect is aggravated by the gradual loss of soil nitrogen from LULUC disturbance. Our study implies that (1) nitrogen limitation of CO 2 uptake is substantial and sensitive to nitrogen inputs; (2) if LULUC emissions are larger than previously estimated in studies without nitrogen limitation, then meeting the same climate mitigation target would require an equivalent additional reduction of fossil fuel emissions; (3) the effectiveness of land‐based mitigation strategies will critically depend on the interactions between nutrient limitations and secondary forests resulting from LULUC; and (4) it is important for terrestrial biosphere models to consider nitrogen constraint in estimates of the strength of future land carbon uptake.

Meiyappan, Prasanth↗

Interactions between land use change and carbon cycle feedbacks: Land Use and Carbon Cycle Feedbacks

We explore the role of human land use and land cover change (LULCC) in modifying the terrestrial carbon budget in simulations forced by Representative Concentration Pathway 8.5, extended to year 2300 by using the Community Earth System Model, . Overall, conversion of land (e.g., from forest to croplands via deforestation) results in a model-estimated, cumulative carbon loss of 490 Pg C between 1850 and 2300, larger than the 230 Pg C loss of carbon caused by climate change over this same interval. The LULCC carbon loss is a combination of a direct loss at the time of conversion and an indirect loss from the reduction of potential terrestrial carbon sinks. Approximately 40% of the carbon loss associated with LULCC in the simulations arises from direct human modification of the land surface; the remaining 60% is an indirect consequence of the loss of potential natural carbon sinks. Because of the multicentury carbon cycle legacy of current land use decisions, a globally averaged amplification factor of 2.6 must be applied to 2015 land use carbon losses to adjust for indirect effects. This estimate is 30% higher when considering the carbon cycle evolution after 2100. Most of the terrestrial uptake of anthropogenic carbon in the model occurs from the influence of rising atmospheric CO 2 on photosynthesis in trees, and thus, model-projected carbon feedbacks are especially sensitive to deforestation.

58 GEOSCIENCES↗

A case study of microphysical structures and hydrometeor phase in convection using radar Doppler spectra at Darwin, Australia

To understand the microphysical processes that impact diabatic heating and cloud lifetimes in convection, we need to characterize the spatial distribution of supercooled liquid water. To address this observational challenge, vertically pointing active sensors at the Darwin Atmospheric Radiation Measurement (ARM) site are used to classify cloud phase within a deep convective cloud in a shallow to deep convection transitional case. The cloud cannot be fully observed by a lidar due to signal attenuation. Thus we develop an objective method for identifying hydrometeor classes, including mixed-phase conditions, using k-means clustering on parameters that describe the shape of the Doppler spectra from vertically pointing Ka band cloud radar. This approach shows that multiple, overlapping mixed-phase layers exist within the cloud, rather than a single region of supercooled liquid, indicating complexity to how ice growth and diabatic heating occurs in the vertical structure of the cloud.

54 ENVIRONMENTAL SCIENCES↗