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At least 577 records · Page 32

Mitigating the Impacts of Measurement Error in the Quesst Mission Community Noise Study

Beginning in 2025, the NASA Quesst mission will conduct a series of community response tests involving flyovers of the X-59 aircraft at select localities across the United States. Several waves of a longitudinal survey will be administered over approximately one month of testing in order to capture perceptual responses to low-amplitude sonic booms, or “sonic thumps”. Simultaneously, noise exposure levels will be estimated by fusing model-based predictions with measurements taken from a sparse network of monitors in the region. As one of the aims of the study is to produce a dose-response curve, a regression model relating perceptual response to noise exposure levels, it is important to acknowledge the potential attenuation bias that results from measurement error in the estimated noise exposure levels. In this presentation we review and compare several methods for dealing with measurement error in generalized linear mixed models. The methods are demonstrated on simulated data and real data collected during past NASA risk reduction studies.

measurement error↗

Bias Correction and Statistical Downscaling of Solar Radiation Using NA-CORDEX and the NSRDB

The current state-of-art for estimating long-term PV production uses long-term estimates of solar radiation variables, such as global horizontal irradiance (GHI), from previous years. This data is used in models such as the System Advisor Model (SAM) or PYSyst to predict annual production for a PV plant. This information is then used to estimate the production over the next 20 years (a typical plant lifetime) under the assumption that the variability over the current period is representative of the future. As the PV industry moves to extend plant lifetimes to 50 years the current assumptions of representativeness of weather may not be appropriate. This is especially true as our climate changes rapidly. To assess long-term PV production, future projections for solar radiation based on projected carbon emissions are readily available in regional and global climate models. However, climate model projections contain inherent biases that may need to be corrected for accurate analysis of future projections of climate variables. Several studies have analyzed projections of solar radiation for future years, however the accuracy of the model output compared to current and historic data has not been widely studied. Chen (2021) showed that available climate models do not accurately represent solar radiation in some cases, over-projecting GHI at the surface while under-projecting its obstructions, such as clouds and aerosols. This works aims to (1) increase understanding of the accuracy of solar radiation currently available in global and regional climate models and (2) implement bias correction through linear models based on reanalysis data compared to observed solar radiation. The latter aim will be conducted using available observed solar radiation data and modeled data from several regional climate models (RCMs). The bias correction method will be applied to projections of solar radiation resulting in a more accurate representation of the future of solar production.

climate data↗

Machine learning modeling and model predictive control of a closed-circuit reverse osmosis system

Closed-circuit reverse osmosis (CCRO) offers a flexible and energy-efficient alternative to conventional reverse osmosis by operating in a semi-batch mode that recycles brine, enabling higher recovery rates and reduced specific energy consumption (SEC). However, developing accurate, system-level dynamic models for CCRO remains challenging due to its nonlinear, multi-phase operation and sensitivity to variable feed water conditions. Traditional modeling approaches, such as NARMAX (nonlinear autoregressive moving average with exogenous inputs), often struggle to generalize across varying inlet feed concentrations, necessitating frequent parameter re-estimation and limiting their utility for real-time control applications. To address these limitations, we developed a long short-term memory (LSTM) neural network model trained on an extensive experimental data set from a CCRO pilot plant. The model accepts three inputs, feed flow rate, recirculation flow rate, and initial feed conductivity, and predicts three key outputs: reject conductivity, feed pump power draw, and recirculation pump power draw. We validated the LSTM model against experimental data, demonstrating its ability to distinguish between different feed conductivities and adapt to variable flow rates. Subsequently, we incorporated the LSTM model within a nonlinear model predictive control (MPC) scheme and conducted closed-loop simulations to optimize the integrated SEC (iSEC). In conclusion, the results project up to a 6% reduction in iSEC by using MPC to optimize performance over the entire experiment duration, without requiring any random excitation for data collection or parameter re-estimation.

Desalination↗

Recent Changes in High-Latitude Glaciers, Ice Caps, and Ice Sheets

The glaciers and ice sheets of the world contain enough ice to raise sea level by approximately 70 meters if they were to disappear entirely, and most of this ice is located in the climatically sensitive polar regions. Fortunately changes of this magnitude would probably take many thousands of years to occur, but recent discoveries indicate that these ice masses are responding to changes in today s climate more rapidly than previously thought. These responses are likely to be of great societal significance, primarily in terms of their implications for sea level, but also in terms of how their discharge of freshwater, through melting or calving, may impact ocean circulation. For millions of years, oceans have risen and fallen as the Earth has warmed and cooled, and ice on land has shrunk and grown. Today is no different in that respect, as sea levels have been rising at a rate of nearly 2 m per year during the last century (Miller and Douglas 2004), and 3 mm/yr in the last 12 years (Leuliette et al. 2004). What is different today, however, is that tens - perhaps hundreds - of millions of people live in coastal areas that are vulnerable to changes in sea level. Rising seas erode beaches, increase flood potential, and reduce the ability of barrier islands and coastal wetlands to mitigate the effects of major storms and hurricanes. The costs associated with a one-meter rise in sea level are estimated to be in the hundreds of billions of dollars in the United States alone. The worldwide costs in human terms would be far greater as some vulnerable low-lying coastal regions would become inundated, especially in poorer nations that do not have the resources to deal with such changes. Such considerations are particularly important in light of the fact that a one meter sea level rise is not significantly outside the 0.09 to 0.88 range of predictions for this century (IPCC 2001), and rises of this magnitude have occurred in the past in as little as 20 years (Fairbanks 1989). While the expansion of the warming oceans is estimated to be about a third of recent sea level rise, (Miller and Douglas 2004) the greatest potential for significantly increasing sea level lies in the Greenland and Antarctic ice sheets. For different reasons, each exhibits characteristics that suggest they are potentially unstable. In Antarctica, large portions of the ice cover rest on a soft bed that lies below sea level, making it vulnerable to runaway retreat. The Greenland ice sheet experiences considerable melt, which has the potential to rapidly accelerate the flow of ice toward the sea. While smaller ice masses, such as the Alaskan Glaciers and the Canadian ice caps, do not have anywhere near the same potential to impact sea level as the vast ice sheets do, many are melting rapidly, posing a significant near-term threat.

Abdalati, Waleed↗

Expansion of the Real-time Sport-land Information System for NOAA / National Weather Service Situational Awareness and Local Modeling Applications

The NASA Short-term Prediction Research and Transition (SPoRT) Center in Huntsville, AL (Jedlovec 2013; Ralph et al. 2013; Merceret et al. 2013) is running a real-time configuration of the Noah land surface model (LSM) within the NASA Land Information System (LIS) framework (hereafter referred to as the "SPoRT-LIS"). Output from the real-time SPoRT-LIS is used for (1) initializing land surface variables for local modeling applications, and (2) displaying in decision support systems for situational awareness and drought monitoring at select NOAA/National Weather Service (NWS) partner offices. The SPoRT-LIS is currently run over a domain covering the southeastern half of the Continental United States (CONUS), with an additional experimental real-time run over the entire CONUS and surrounding portions of southern Canada and northern Mexico. The experimental CONUS run incorporates hourly quantitative precipitation estimation (QPE) from the National Severe Storms Laboratory Multi- Radar Multi-Sensor (MRMS) product (Zhang et al. 2011, 2014), which will be transitioned into operations at the National Centers for Environmental Prediction (NCEP) in Fall 2014. This paper describes the current and experimental SPoRT-LIS configurations, and documents some of the limitations still remaining through the advent of MRMS precipitation analyses in the SPoRT-LIS land surface model (LSM) simulations. Section 2 gives background information on the NASA LIS and describes the realtime SPoRT-LIS configurations being compared. Section 3 presents recent work done to develop a training module on situational awareness applications of real-time SPoRT-LIS output. Comparisons between output from the two SPoRT-LIS runs are shown in Section 4, including a documentation of issues encountered in using the MRMS precipitation dataset. A summary and future work in given in Section 5, followed by acknowledgements and references.

Case, Jonathan L.↗

Analysis of vibronic transitions in titanium doped sapphire using the temperature of the fluorescence spectra

An analysis of the fluorescence spectra of titanium-doped sapphire crystals for temperatures ranging from 13 to 578 K is made. Zero- and multiphoton assisted electronic transitions are observed at temperatures below 125 K. Zero-phonon transition energies agree with previously reported measured and predicted values. Photon-assisted transitions suggest that two principle modes of lattice vibrations with energies of 220 and 260/cm are coupled to the electronic 2T2g state. A single phonon energy of 173/cm is observed to couple to the 2Eg electronic state. Crossover energy is estimated to be about 11,800/cm using a simple harmonic approximation. Lineshape analysis is performed. The fluorescence lifetime as measured to be a constant 3.9 microsec below 150 k decreasing to 2.9 microsec at 300 K.

Byvik, C. E.↗

An analytical and experimental investigation of output feedback vs. linear quadratic regulator

This paper presents analytical and experimental comparison of three control laws for a laboratory structure designed to simulate large space structures. The first control law is the standard time invariant linear quadratic regulator with state estimation, which requires model reduction for practical implementation. This model reduction is associated with the so-called spillover instability. Two new simple direct output feedback control laws guaranteeing stability are proposed. One minimizes the maximum control force, and the other minimizes the same quadratic performance index as the linear quadratic regulator. The three control laws are found to give comparable performance for the modes retained in the reduced model. However, the standard linear quadratic regulator with state estimation provides almost no margin of stability for the unmodeled modes, while the simpler direct feedback laws provide significant stability margins to all modes. The analytical results were verified experimentally using a digital implementation of the control laws. Good agreement between the analytical predictions and experimental measurements was observed.

Martinovic, Zoran N.↗

Pointing a ground antenna at a spinning spacecraft using Conscan-simulation results

The results are presented for an investigation of ground antenna pointing errors which are caused by fluctuations of the receiver AGC signal due to thermal noise and a spinning spacecraft. Transient responses and steady-state errors and losses are estimated using models of the digital Conscan (conical scan) loop, the FFT, and antenna characteristics. Simulation results are given for the on-going Voyager mission and for the upcoming Galileo mission, which includes a spinning spacecraft. The simulation predicts a 1 sigma pointing error of 0.5 to 2.0 mdeg for Voyager, assuming an AGC loop SNR of 35 to 30 dB with a scan period varying from 128 to 32 sec, respectively. This prediction is in agreement with the DSS 14 antenna Conscan performance of 1.7 mdeg for 32 sec scans as reported in earlier studies. The simulation of Galileo predicts 1 mdeg error with a 128 sec scan and 4 mdeg with a 32 sec scan under similar AGC conditions.

Mileant, A.↗

System identification requirements for high-bandwidth rotorcraft flight control system design

The application of system identification methods to high-bandwidth rotorcraft flight control system design is examined. Flight test and modeling requirements are illustrated using flight test data from a BO-105 hingeless rotor helicopter. The proposed approach involves the identification of nonparametric frequency-response models followed by parametric (transfer funtion and state space) model identification. Results for the BO-105 show the need for including coupled body/rotor flapping and lead-lag dynamics in the identification model structure to allow the accurate prediction of control system bandwidth limitations. Lower-order models are useful for estimating nominal control system performance only when the flight data used for the identification are band-limited to be consistent with the frequency range of applicability of the model. The flight test results presented in this paper are consistent with theoretical studies by previous researchers.

Tischler, Mark B.↗

Pointing a ground antenna at a spinning spacecraft using conical scan - Simulation results

The results are presented for an investigation of ground antenna pointing errors which are caused by fluctuations of the receiver AGC signal due to thermal noise and a spinning spacecraft. Transient responses and steady-state errors and losses are estimated using models of the digital Conscan (conical scan) loop, the FFT, and antenna characteristics. Simulation results are given for the on-going Voyager mission and for the upcoming Galileo mission, which includes a spinning spacecraft. The simulation predicts a 1 sigma pointing error of 0.5 to 2.0 mdeg for Voyager, assuming an AGC loop SNR of 35 to 30 dB with a scan period varying from 128 to 32 sec, respectively. This prediction is in agreement with the DSS 14 antenna Conscan performance of 1.7 mdeg for 32 sec scans as reported in earlier studies. The simulation of Galileo predicts 1 mdeg error with a 128 sec scan and 4 mdeg with a 32 sec scan under similar AGC conditions.

Mileant, Alexander↗

Efficient Evaluation and Optimization of Structural Reliability

Use of approximations for calculating the structural failure probability under uncertainties is a necessary aspect. But efficient use of suitable approximations at different stages of reliability prediction and design makes this valuable tool practical for many large scale structures. This research addresses the modern approximation concepts and their utility in structural reliability estimation. Emphasis is placed on building higher order approximations using intervening variables to closely represent the nonlinear limit state functions. Several test problems with highly nonlinear performance functions are used to demonstrate the accuracy of the proposed method. Many of the structural problems are modeled and simulated using the finite element methods (FEM) for obtaining a detailed structural response. FEM is a computationally intensive numerical procedure with a large number of degrees of freedom. With an increase in the complexity of the structural model and the multidisciplinary nature of analyses, the number of limit states and their computation increases very significantly. The requirement of frequent repetitive analysis of the structure hinders the utility of any tool and discourages that approach from being used. One particular tool which faces this difficulty is the computation of the structural reliability under parametric uncertainties.

Grandhi, Ramana V.↗

Intermediate Temperature Stress Rupture of Woven SiC Fiber, BN Interphase, SiC Matrix Composites in Air

Tensile stress-rupture experiments were performed on woven Hi-Nicalon reinforced SiC matrix composites with BN interphases in air. Modal acoustic emission (AE) was used to monitor the damage accumulation in the composites during the tests and microstructural analysis was performed to determine the amount of matrix cracking that occurred for each sample. Fiber fractograph), was also performed for individual fiber failures at the specimen fracture surface to determine the strengths at which fibers failed. The rupture strengths were significantly worse than what would have been expected front the inherent degradation of the fibers themselves when subjected to similar rupture conditions. At higher applied stresses the rate of rupture "?as larger than at lower applied stresses. It was observed that the change in rupture rate corresponded to the onset of through-thickness cracking in the composites themselves. The primary cause of the sen,ere degradation was the ease with which fibers would bond to one another at their closest separation distances, less than 100 nanometers, when exposed to the environment. The near fiber-to-fiber contact in the woven tows enabled premature fiber failure over large areas of matrix cracks due to the stress-concentrations created b), fibers bonded to one another after one or a few fibers fail. i.e. the loss of global load sharing. An@, improvement in fiber-to-fiber separation of this composite system should result in improved stress- rupture properties. A model was den,eloped in order to predict the rupture life-time for these composites based on the probabilistic nature of indin,idual fiber failure at temperature. the matrix cracking state during the rupture test, and the rate of oxidation into a matrix crack. Also incorporated into the model were estimates of the stress-concentration that would occur between the outer rim of fibers in a load-bearing bundle and the unbridged region of a matrix crack after Xia et al. For the lower stresses, this source of stress-concentration was the likely cause for initial fiber failure that would trigger catastrophic failure of the composite.

Morscher, Gregory N.↗

NCA-LDAS: Overview and Analysis of Hydrologic Trends for the National Climate Assessment

Terrestrial hydrologic trends over the conterminous United States are estimated for 1980-47 2015 using the National Climate Assessment-Land Data Assimilation System (NCA-LDAS) reanalysis. NCA-LDAS employs the uncoupled Noah Version 3.3 land surface model at 0.125 degreesx0.125 degrees forced with NLDAS-2 meteorology, rescaled Climate Prediction Center precipitation, and assimilated satellite-based soil moisture, snow depth and irrigation products. Mean annual trends are reported using the nonparametric Mann-Kendall test at p<0.1 significance. Results illustrate the interrelationship between regional gradients in forcing trends, and trends in other land energy and water stores and fluxes. Mean precipitation trends range from +3 to +9 mm/yr in the Upper Great Plains and Northeast to -1 to -9 in the West and South; net radiation flux trends range from +0.05 to +0.20 W/m(exp2)/yr in the East to -0.05 to -0.20 in the West; U.S.-wide temperature trends average about +0.03K/yr. Trends in soil moisture, snow cover, latent and sensible heat fluxes and runoff are consistent with forcings, contributing to increasing evaporative fraction trends from West to East. Evaluation of NCA-LDAS trends compared to independent data indicates mixed results. The RMSE of U.S.-wide trends in number of snow cover days improved from 3.13 to 2.89 days/yr while trend detection increased 11%; Trends in latent heat flux were hardly affected, RMSE decreasing only 0.17 to 0.16 W/m(exp 2)/yr, while trend detection increased 2%; NCA-LDAS runoff trends degraded significantly from 2.6 to 16.1 mm/yr while trend detection was unaffected. Analysis also indicated that NCA-LDAS exhibits relatively more skill in low precipitation station density areas, suggesting there are limits to the effectiveness of satellite data assimilation in densely gaged regions. Overall, NCA-LDAS demonstrates capability for quantifying physically consistent, U.S. hydrologic climate trends over the satellite era.

Snow depth↗

Skylab S-193 radar altimeter experiment analyses and results

The design of optimum filtering procedures for geoid recovery is discussed. Statistical error bounds are obtained for pointing angle estimates using average waveform data. A correlation of tracking loop bandwidth with magnitude of pointing error is established. The impact of ocean currents and precipitation on the received power are shown to be measurable effects. For large sea state conditions, measurements of sigma 0 deg indicate a distinct saturation level of about 8 dB. Near-nadir less than 15 deg values of sigma 0 deg are also presented and compared with theoretical models. Examination of Great Salt Lake Desert scattering data leads to rejection of a previously hypothesized specularly reflecting surface. Pulse-to-pulse correlation results are in agreement with quasi-monochromatic optics theoretical predictions and indicate a means for estimating direction of pointing error. Pulse compression techniques for and results of estimating significant waveheight from waveform data are presented and are also shown to be in good agreement with surface truth data. A number of results pertaining to system performance are presented.

Brown, G. S.↗

Current state and future projections of drying processes in the US food and pulp and paper sectors: Energy, economic, and environmental assessment

The pulp and paper (P/P) and food sectors are the third- and fifth-largest industrial energy consumers in the United States, with total on-site energy consumption of 2,039 TBtu and 1,144 TBtu, respectively. Thermal drying processes for moisture removal, which are energy-intensive, play a critical role in both industries. This study is the first to evaluate state- and national-level US drying energy demand for these sectors from 2020 to 2050. To complete this evaluation, we developed a thermodynamic modeling framework integrated with economic and environmental models to compute product-specific drying energy intensity and estimate the sector-specific costs and emissions profiles associated with drying operations. The model-predicted energy intensity was validated against the literature. Using current and projected annual production volumes in these sectors, we estimated total drying energy use. Results indicate that drying accounts for 22 % of total energy consumption in the P/P sector and 10 % in the food sector. The estimated annual energy cost (2020) to operate thermal dryers is $\$$919 M in the P/P sector and $\$$417 M in the food sector. Additionally, drying contributes to 25 % of total CO 2 e emissions in the P/P sector (including biogenic) and 15 % of emissions in the food sector. Regional performance shows that the Southern US is the leading energy consumer for P/P drying, whereas the Midwest leads in food drying. This study presents both potential solutions to enhance drying efficiency and barriers to implementation. Energy efficiency improvements, low-carbon fuels, and electrification are discussed as key pathways for reducing costs and optimizing industrial drying processes.

3E analysis↗

How Well Do We Know the Neutron-Matter Equation of State at the Densities Inside Neutron Stars? A Bayesian Approach with Correlated Uncertainties

Here, we introduce a new framework for quantifying correlated uncertainties of the infinite-matter equation of state derived from chiral effective field theory (𝜒⁢EFT ). Bayesian machine learning via Gaussian processes with physics-based hyperparameters allows us to efficiently quantify and propagate theoretical uncertainties of the equation of state, such as 𝜒⁢EFT truncation errors, to derived quantities. We apply this framework to state-of-the-art many-body perturbation theory calculations with nucleon-nucleon and three-nucleon interactions up to fourth order in the 𝜒⁢EFT expansion. This produces the first statistically robust uncertainty estimates for key quantities of neutron stars. We give results up to twice nuclear saturation density for the energy per particle, pressure, and speed of sound of neutron matter, as well as for the nuclear symmetry energy and its derivative. At nuclear saturation density, the predicted symmetry energy and its slope are consistent with experimental constraints.

79 ASTRONOMY AND ASTROPHYSICS↗

A statistical and simulation-informed model for estimating permeability from pore size distribution in saturated geomaterials

Accurate permeability estimation is essential across subsurface engineering applications but remains challenging due to the complex pore structures of natural geomaterials. Traditional empirical methods and simplified theoretical models often inadequately capture the role of pore size distribution and connectivity. Here, this study develops a statistical and simulation-informed permeability model that collapses pore-scale complexity into a compact scaling of the form k = αϕμ d 2 , where ϕ is porosity, μ d is mean pore size, and α is a weakly varying coefficient. By combining pore network simulations with statistical analysis of unimodal and bimodal pore size distributions, we identify three key findings: (i) permeability is much more sensitive to mean pore size than to porosity; (ii) across extensive datasets, the ratio σ d /μ d (standard deviation to mean) clusters around a characteristic value ∼0.4, allowing the effects of the full pore size distribution to be represented by μ d and a narrowly varying α ≈ 0.05; and (iii) for bimodal systems, there exists a critical fraction of small pores ∼0.78 above which flow becomes small-pore dominated, enabling the definition of an effective flow-controlling pore population and facilitating simplified permeability estimation for such systems. The resulting model, which requires only porosity and a representative mean pore size as inputs, is validated against comprehensive experimental datasets (>1700 samples) spanning diverse soils and rocks and achieves good predictive accuracy. Overall, this work provides a physically grounded yet practically simple permeability estimator suitable for subsurface engineering, environmental protection, and resource management applications.

Permeability↗

National and regional waste stream in the United States: conformance and disparity

Accurate estimation of municipal solid waste (MSW) composition is critical for efficient waste management. In the United States, site-specific and material flow approaches determine the MSW composition at regional and national levels. The material flow-based national estimates are determined by the US EPA; the US EPA’s estimates are known to differ substantially from the aggregated tonnage of MSW managed by waste handling facilities in the United States. However, the material class-specific discrepancies of the US EPA’s material flow approach resulting in these differences are unknown. To find the basis of these discrepancies, we analyze the discarded MSW stream of 27 US states, which roughly accounts for 73 percent of the US population. Our analysis indicates that the material flow-based national estimates are accurate for the food, plastic, and glass material classes. In contrast, we find that the US EPA’s material flow-based predictions underestimate paper waste disposal by at least 15 million tons annually. These differences likely stem from incorrect assumptions of residence time. These results highlight the material class-specific strengths and drawbacks of the US EPA’s material flow-based MSW estimates.

29 ENERGY PLANNING, POLICY, AND ECONOMY↗