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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.

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At least 271 records · Page 15
All sourcesNASA NTRSDOE OSTI
DOE OSTI2020

Real-time Ridesharing for Transportation Hubs with Demand and Supply Uncertainty

Transportation hubs in major cities generate a significant amount of trips by taxis and for-hail vehicles (FHV), with many of the trips sharing similar destinations. This suggests promising opportunities to leverage the collective travel needs with dedicated ridesharing solutions to reduce the externalities of excessive traffic at transportation hubs. In this study, we develop a novel dynamic ridesharing approach to serve trips from the transportation hub by considering (1) demand (new passengers) and supply (newly available vehicles) in the near future and (2) the uncertainty of future predictions. Our approach consists of two stages. In the first stage, we develop a data structure called hub mobility tree to generate potential combinations of shareable trips as candidate schedules efficiently. Then the generated schedules are used in the second stage to formulate the stochastic hub-based ridesharing problem (SHRP), which is a stochastic integer programming problem with the objective to maximize the total expected ridesharing profit over time. Due to the prohibitive number of shareable trips, we then approximately solve SHRP by the sample average approximate method (SAA), and a dual Lagrangian technique is implemented to further improve the scalability of the solution approach. We demonstrate the performances of the proposed method by simulating the ridesharing service at JFK airport using NYC taxi and FHV data. The results indicate that the proposed method outperforms the myopic ridesharing (maximize profit for a single time step) and the rolling horizon method with point estimation of future demand and supply.

dynamic ridesharing↗
DOE OSTI2024

Using Median Point in Keeling Plot to Reduce the Uncertainty of the Isotopic Composition of Evapotranspiration

Abstract The isotopic composition of evapotranspirationδ ET is a crucial parameter in isotope-based evapotranspiration (ET) partitioning and moisture recycling studies. The Keeling plot method is the most prevalent method to calculateδ ET , though it contains large extrapolated uncertainties from the least squares regression. Traditional Keeling regression uses the mean point of individual measurements. Here, a modified Keeling plot framework was proposed using the median point of individual measurements. We tested theδ ET uncertainty using the mean point [σ ET (mean)] and median point [σ ET (median)]. Multiple resolutions of input and output data from six independent sites were used to test the performance of the two methods. Theσ ET (mean) would be greater thanσ ET (median) when the mean value of inverse vapor concentration () is greater than the median value of inverse vapor concentration []. When applying the filter ofr 2 > 0.8, around 70% ofσ ET (mean) was greater thanσ ET (median). This phenomenon might be due to the normality of the vapor concentrationC υ producing the asymmetric distribution of 1/C υ . The median method could perform significantly better than the mean method when inputting high-resolution measurements (e.g., 1 Hz) and when the water vapor concentrationC υ is relatively low. Compared to the mean method, applying the median method could on average reduce 6.88% of ET partitioning uncertainties and could on average reduce 9.00% of moisture recycling uncertainties. This study provided a new insight of the Keeling plot method and emphasized handling model output uncertainty from multiple perspectives instead of only from input parameters.

Meteorology & Atmospheric Sciences↗
DOE OSTI2025

An interregional optimization approach for time series aggregation in continent-scale electricity system models

Modeling electric power systems with high shares of weather-dependent resources requires tradeoffs between temporal, spatial, and operational resolution. Many studies perform time series aggregation using clustering algorithms to reduce the temporal dimension, but when modeling continent-scale electricity systems that are large enough to contain multiple independent weather systems, this approach requires large numbers of representative periods to minimize errors in regional wind and solar capacity factors. Here, a new optimization-based approach for representative period selection and weighting is introduced that minimizes regional errors in average renewable capacity factors and electricity demand. The method delivers higher regional fidelity with fewer representative periods than alternative clustering methods when applied to wind, solar, and demand profiles for the contiguous United States. When representative periods are selected from multiple weather years, the optimized method reproduces regional averages with lower error than a complete 365-day time series from any single weather year. The method identifies only representative (as opposed to outlying) periods but can be combined with an iterative "stress period" identification approach to guide efficient decision-making considering both average and high-risk weather conditions.

24 POWER TRANSMISSION AND DISTRIBUTION↗
DOE OSTI2021

Propagation of priors for more accurate and efficient spectroscopic functional fits and their application to ferroelectric hysteresis

Multi-dimensional spectral-imaging is a mainstay of the scanning probe and electron microscopies, micro-Raman, and various forms of chemical imaging. In many cases, individual spectra can be fit to a specific functional form, with the model parameter maps, providing direct insight into material properties. Since spectra are often acquired across a spatial grid of points, spatially adjacent spectra are likely to be similar to one another; yet, this fact is almost never used when considering parameter estimation for functional fits. On datasets tried here, we show that by utilizing proximal information, whether it be in the spatial or spectral domains, it is possible to improve the reliability and increase the speed of such functional fits by ~2-3x, as compared to random priors. We explore and compare three distinct new methods: (1) spatially averaging neighborhood spectra, and propagating priors based on functional fits to the averaged case, (2) hierarchical clustering-based methods where spectra are grouped hierarchically based on response, with the priors propagated progressively down the hierarchy, and (3) regular clustering without hierarchical methods with priors propagated from fits to cluster means. Our results highlight that utilizing spatial and spectral neighborhood information is often critical for accurate parameter estimation in noisy environments, which we show for ferroelectric hysteresis loops acquired on a prototypical PbTiO3 thin film with piezoresponse spectroscopy. This method is general and applicable to any spatially measured spectra where functional forms are available. Examples include exploring the superconducting gap with tunneling spectroscopy, using the Dynes formula, or current-voltage curve fits in conductive atomic force microscopy mapping. Here we explore the problem for ferroelectric hysteresis, which, given its large parameter space, constitutes a more difficult task than, for example, fitting current-voltage curves with a Schottky emission formula.

42 ENGINEERING↗
NASA NTRS2004

New Reduced Two-Time Step Method for Calculating Combustion and Emission Rates of Jet-A and Methane Fuel With and Without Water Injection

A simplified kinetic scheme for Jet-A, and methane fuels with water injection was developed to be used in numerical combustion codes, such as the National Combustor Code (NCC) or even simple FORTRAN codes that are being developed at Glenn. The two time step method is either an initial time averaged value (step one) or an instantaneous value (step two). The switch is based on the water concentration in moles/cc of 1x10(exp -20). The results presented here results in a correlation that gives the chemical kinetic time as two separate functions. This two step method is used as opposed to a one step time averaged method previously developed to determine the chemical kinetic time with increased accuracy. The first time averaged step is used at the initial times for smaller water concentrations. This gives the average chemical kinetic time as a function of initial overall fuel air ratio, initial water to fuel mass ratio, temperature, and pressure. The second instantaneous step, to be used with higher water concentrations, gives the chemical kinetic time as a function of instantaneous fuel and water mole concentration, pressure and temperature (T4). The simple correlations would then be compared to the turbulent mixing times to determine the limiting properties of the reaction. The NASA Glenn GLSENS kinetics code calculates the reaction rates and rate constants for each species in a kinetic scheme for finite kinetic rates. These reaction rates were then used to calculate the necessary chemical kinetic times. Chemical kinetic time equations for fuel, carbon monoxide and NOx were obtained for Jet-A fuel and methane with and without water injection to water mass loadings of 2/1 water to fuel. A similar correlation was also developed using data from NASA's Chemical Equilibrium Applications (CEA) code to determine the equilibrium concentrations of carbon monoxide and nitrogen oxide as functions of overall equivalence ratio, water to fuel mass ratio, pressure and temperature (T3). The temperature of the gas entering the turbine (T4) was also correlated as a function of the initial combustor temperature (T3), equivalence ratio, water to fuel mass ratio, and pressure.

Molnar, Melissa↗
NASA NTRS2005

Simplified Two-Time Step Method for Calculating Combustion and Emission Rates of Jet-A and Methane Fuel With and Without Water Injection

A simplified kinetic scheme for Jet-A, and methane fuels with water injection was developed to be used in numerical combustion codes, such as the National Combustor Code (NCC) or even simple FORTRAN codes. The two time step method is either an initial time averaged value (step one) or an instantaneous value (step two). The switch is based on the water concentration in moles/cc of 1x10(exp -20). The results presented here results in a correlation that gives the chemical kinetic time as two separate functions. This two time step method is used as opposed to a one step time averaged method previously developed to determine the chemical kinetic time with increased accuracy. The first time averaged step is used at the initial times for smaller water concentrations. This gives the average chemical kinetic time as a function of initial overall fuel air ratio, initial water to fuel mass ratio, temperature, and pressure. The second instantaneous step, to be used with higher water concentrations, gives the chemical kinetic time as a function of instantaneous fuel and water mole concentration, pressure and temperature (T4). The simple correlations would then be compared to the turbulent mixing times to determine the limiting rates of the reaction. The NASA Glenn GLSENS kinetics code calculates the reaction rates and rate constants for each species in a kinetic scheme for finite kinetic rates. These reaction rates are used to calculate the necessary chemical kinetic times. Chemical kinetic time equations for fuel, carbon monoxide and NOx are obtained for Jet-A fuel and methane with and without water injection to water mass loadings of 2/1 water to fuel. A similar correlation was also developed using data from NASA's Chemical Equilibrium Applications (CEA) code to determine the equilibrium concentrations of carbon monoxide and nitrogen oxide as functions of overall equivalence ratio, water to fuel mass ratio, pressure and temperature (T3). The temperature of the gas entering the turbine (T4) was also correlated as a function of the initial combustor temperature (T3), equivalence ratio, water to fuel mass ratio, and pressure.

Molnar, Melissa↗
DOE OSTI2026

Accurate energies for ππ* excited states via exchange scaling: the XS-CASSCF method

The state-averaged complete-active space self-consistent field method (SA-CASSCF) is a widely employed electronic structure method used for studying photochemistry and dynamics owing to its ability to provide a reliable description even of complicated cases while still retaining computational efficiency. However, SA-CASSCF suffers from one Achilles heel, related to the description of ionic ππ* excited states, whose energy is often overestimated by 1–2 eV. In light of this challenge, we present the XS-CASSCF method, a new approach based on the idea of exchange scaling (XS) that screens the involved energy terms to improve the excitation energies of singlet ionic ππ* states. First, we illustrate the power of the XS-CASSCF method using hexatriene and para-quinodimethane as examples, showing that it corrects the targeted ionic states while leaving the other states largely unaffected, giving root-mean-square errors (RMSE) below 0.2 eV for the four lowest states in both cases. Subsequently, XS-CASSCF vertical excitation energies are tested against theoretical best estimates for a set of 11 molecules and 56 excited states. XS-CASSCF performs exceptionally well for the ππ* states of hydrocarbons, reducing the RMSE over 21 excitation energies from 0.96 to 0.27 eV. In the challenging subset of molecules with heteroatoms and a larger number of ππ* and nπ* states, we find that improvements can also be obtained, albeit not as pronounced. We conclude with an outlook into more realistic molecular materials focusing on their singlet–triplet (S 1 /T 1 ) gaps, finding that significant improvements can be obtained along the whole range of S 1 /T 1 gaps studied, going from 0.1 eV to more than 1.5 eV. Owing to notable improvements across significant classes of molecules combined with its conceptual simplicity, we believe that XS-CASSCF is a promising addition to the electronic structure toolbox, serving both as a standalone electronic structure method and as a starting point for further correlated treatment.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2020

Towards Off-policy Evaluation as a Prerequisite for Real-world Reinforcement Learning in Building Control

We present an initial study of off-policy evaluation (OPE), a problem prerequisite to real-world reinforcement learning (RL), in the context of building control. OPE is the problem of estimating a policy's performance without running it on the actual system, using historical data from the existing controller. It enables the control engineers to ensure a new, pretrained policy satisfies the performance requirements and safety constraints of a real-world system, prior to interacting with it. While many methods have been developed for OPE, no study has evaluated which ones are suitable for building operational data, which are generated by deterministic policies and have limited coverage of the state-action space. After reviewing existing works and their assumptions, we adopted the approximate model (AM) method. Furthermore, we used bootstrapping to quantify uncertainty and correct for bias. In a simulation study, we evaluated the proposed approach on 10 policies pretrained with imitation learning. On average, the AM method estimated the energy and comfort costs with 1.84% and 14.1% error, respectively.

Chen, B↗
NASA NTRS1980

Calculation of power spectrums from digital time series with missing data points

Two algorithms are developed for calculating power spectrums from the autocorrelation function when there are missing data points in the time series. Both methods use an average sampling interval to compute lagged products. One method, the correlation function power spectrum, takes the discrete Fourier transform of the lagged products directly to obtain the spectrum, while the other, the modified Blackman-Tukey power spectrum, takes the Fourier transform of the mean lagged products. Both techniques require fewer calculations than other procedures since only 50% to 80% of the maximum lags need be calculated. The algorithms are compared with the Fourier transform power spectrum and two least squares procedures (all for an arbitrary data spacing). Examples are given showing recovery of frequency components from simulated periodic data where portions of the time series are missing and random noise has been added to both the time points and to values of the function. In addition the methods are compared using real data. All procedures performed equally well in detecting periodicities in the data.

Murray, C. W., Jr.↗
NASA NTRS1998

A TRMM Rainfall Estimation Method Applicable to Land Areas

Utilizing multi-spectral, dual-polarization Special Sensor Microwave Imager (SSM/I) radiometer measurements, we have developed in this study a method to retrieve average rain rate, R(sub f(sub R)), in a mesoscale grid box of 2deg x 3deg over land. The key parameter of this method is the fractional rain area, f(sub R), in that grid box, which is determined with the help of a threshold on the 85 GHz scattering depression 0 deduced from the SSM/I data. In order to demonstrate the usefulness of this method, nine-months of R(sub f(sub R))are retrieved from SSM/I data over three grid boxes in the Northeastern United States. These retrievals are then compared with the corresponding ground-truth-average rain rate, R(sub g), deduced from 15-minute rain gauges. Based on nine months of rain rate retrievals over three grid boxes, we find that R(sub f(sub R)can explain about 64 % of the variance contained in R(sub g). A similar evaluation of the grid-box-average rain rates R(sub GSCAT) and R(sub SRL), given by the NASA/GSCAT and NOAA/SRL rain retrieval algorithms, is performed. This evaluation reveals that R(sub GSCAT) and R(sub SRL) can explain only about 42 % of the variance contained in R(sub g). In our method, a threshold on the 85 GHz scattering depression is used primarily to determine the fractional rain area in a mesoscale grid box. Quantitative information pertaining to the 85 GHz scattering depression in the grid box is disregarded. In the NASA/GSCAT and NOAA/SRL methods on the other hand, this quantitative information is included. Based on the performance of all three methods, we infer that the magnitude of the scattering depression is a poor indicator of rain rate. Furthermore, from maps based on the observations made by SSM/I on land and ocean we find that there is a significant redundancy in the information content of the SSM/I multi-spectral observations. This leads us to infer that observations of SSM/I at 19 and 37 GHz add only marginal information to that given by 85 GHz scattering depression. As with other methods, the area-average rain retrieval method developed in this study needs tuning with radar and/or rain gauge observations. In the TRMM mission, the microwave radiometer rain retrieval algorithm can be tuned with TRMM radar observations. Since the radiometer has about 3.5 times wider spatial coverage compared to the radar in the TRMM mission, such an algorithm can be useful to extend geographically the rain information provided by the TRMM Precipitation Radar.

Prabhakara, C.↗
NASA NTRS2005

Improved Compression of Wavelet-Transformed Images

A recently developed data-compression method is an adaptive technique for coding quantized wavelet-transformed data, nominally as part of a complete image-data compressor. Unlike some other approaches, this method admits a simple implementation and does not rely on the use of large code tables. A common data compression approach, particularly for images, is to perform a wavelet transform on the input data, and then losslessly compress a quantized version of the wavelet-transformed data. Under this compression approach, it is common for the quantized data to include long sequences, or runs, of zeros. The new coding method uses prefixfree codes for the nonnegative integers as part of an adaptive algorithm for compressing the quantized wavelet-transformed data by run-length coding. In the form of run-length coding used here, the data sequence to be encoded is parsed into strings consisting of some number (possibly 0) of zeros, followed by a nonzero value. The nonzero value and the length of the run of zeros are encoded. For a data stream that contains a sufficiently high frequency of zeros, this method is known to be more effective than using a single variable length code to encode each symbol. The specific prefix-free codes used are from two classes of variable-length codes: a class known as Golomb codes, and a class known as exponential-Golomb codes. The codes within each class are indexed by a single integer parameter. The present method uses exponential-Golomb codes for the lengths of the runs of zeros, and Golomb codes for the nonzero values. The code parameters within each code class are determined adaptively on the fly as compression proceeds, on the basis of statistics from previously encoded values. In particular, a simple adaptive method has been devised to select the parameter identifying the particular exponential-Golomb code to use. The method tracks the average number of bits used to encode recent runlengths, and takes the difference between this average length and the code parameter. When this difference falls outside a fixed range, the code parameter is updated (increased or decreased). The Golomb code parameter is selected based on the average magnitude of recently encoded nonzero samples. The coding method requires no floating- point operations, and more readily adapts to local statistics than other methods. The method can also accommodate arbitrarily large input values and arbitrarily long runs of zeros. In practice, this means that changes in the dynamic range or size of the input data set would not require a change to the compressor. The algorithm has been tested in computational experiments on test images. A comparison with a previously developed algorithm that uses large code tables (generated via Huffman coding on training data) suggests that the data-compression effectiveness of the present algorithm is comparable to the best performance achievable by the previously developed algorithm.

Kiely, Aaron↗
DOE OSTI2024

Multilevel Parareal Algorithm with Averaging for Oscillatory Problems

The present study is an extension of the work done by Peddle, Haut, and Wingate and Haut and Wingate, where a two-level Parareal method with mapping and averaging is examined. The method proposed in this paper is a multilevel Parareal method with arbitrarily many levels, which is not restricted to the two-level case. We give an asymptotic error estimate which reduces to the two-level estimate for the case when only two levels are considered. Introducing more than two levels has important consequences for the averaging procedure, as we choose separate averaging windows for each of the different levels, which is an additional new feature of the present study. The different averaging windows make the proposed method especially appropriate for nonlinear multiscale problems, because we can introduce a level for each intrinsic scale of the problem and adapt the averaging procedure such that we reproduce the behavior of the model on the particular scale resolved by the level. The method is applied to nonlinear differential equations. The nonlinearities can generate a range of frequencies in the problem. The computational cost of the new method is investigated and studied on several examples.

97 MATHEMATICS AND COMPUTING↗
NASA NTRS1976

A method to account for variation of average compressor inlet pressure during instantaneous distortion analyses

Instantaneous distortion analyses compare a time-varying value of an index (or 'surge margin used up') with a critical level (or 'available surge margin' of the compressor) to determine inlet-engine compatibility. Unless freestream conditions or propulsion system controls are changing, it is generally assumed that the available surge margin of the compressor is accurately determined from the steady-state operating point. Results are presented which show that variations of average compressor inlet pressure may occur without changes in freestream conditions or propulsion system controls. The volume dynamics of the compressor will cause these pressure variations to be attenuated and delayed by the time they reach the exit. This will cause the compressor pressure ratio (and available surge margin) to vary with time. A method is presented to calculate the available surge margin as a function of time and incorporate it into an instantaneous distortion analysis. Results show that inlet pressure variations which cause only a small change at the compressor exit can cause a significant variation in the available surge margin.

Burstadt, P. L.↗
DOE OSTI2024

The strong coupling constant: state of the art and the decade ahead

Theoretical predictions for particle production cross sections and decays at colliders rely heavily on perturbative Quantum Chromodynamics (QCD) calculations, expressed as an expansion in powers of the strong coupling constant α$_{S}$. The current O(1%)uncertainty of the QCD coupling evaluated at the reference Z boson mass, αS(mZ2)=0.1179±0.0009, is one of the limiting factors to more precisely describe multiple processes at current and future colliders. A reduction of this uncertainty is thus a prerequisite to perform precision tests of the Standard Model as well as searches for new physics. This report provides a comprehensive summary of the state-of-the-art, challenges, and prospects in the experimental and theoretical study of the strong coupling. The current αS(mZ2)world average is derived from a combination of seven categories of observables: (i) lattice QCD, (ii) hadronic τ decays, (iii) deep-inelastic scattering and parton distribution functions fits, (iv) electroweak boson decays, hadronic final-states in (v) e$^{+}$e$^{−}$, (vi) e–p, and (vii) p–p collisions, and (viii) quarkonia decays and masses. We review the current status of each of these seven αS(mZ2)extraction methods, discuss novel α$_{S}$ determinations, and examine the averaging method used to obtain the world-average value. Each of the methods discussed provides a ‘wish list’ of experimental and theoretical developments required in order to achieve the goal of a per-mille precision on αS(mZ2)within the next decade.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗
NASA NTRS1994

Spin glasses and error-correcting codes

In this article, we study a model for error-correcting codes that comes from spin glass theory and leads to both new codes and a new decoding technique. Using the theory of spin glasses, it has been proven that a simple construction yields a family of binary codes whose performance asymptotically approaches the Shannon bound for the Gaussian channel. The limit is approached as the number of information bits per codeword approaches infinity while the rate of the code approaches zero. Thus, the codes rapidly become impractical. We present simulation results that show the performance of a few manageable examples of these codes. In the correspondence that exists between spin glasses and error-correcting codes, the concept of a thermal average leads to a method of decoding that differs from the standard method of finding the most likely information sequence for a given received codeword. Whereas the standard method corresponds to calculating the thermal average at temperature zero, calculating the thermal average at a certain optimum temperature results instead in the sequence of most likely information bits. Since linear block codes and convolutional codes can be viewed as examples of spin glasses, this new decoding method can be used to decode these codes in a way that minimizes the bit error rate instead of the codeword error rate. We present simulation results that show a small improvement in bit error rate by using the thermal average technique.

Belongie, M. L.↗
NASA NTRS2020

Face- and Cell-Averaged Nodal-Gradient Approach to Cell-Centered Finite-Volume Method on Mixed Grids

In this paper, the averaged nodal-gradient approach previously developed for triangular grids is extended to mixed triangular-quadrilateral grids. It is shown that the face- averaged approach leads to deteriorated iterative convergence on quadrilateral grids. To develop a convergent solver, we consider cell-averaging instead of face-averaging for quadri- lateral cells. We show that the cell-averaged approach leads to a convergent solver and can be efficiently combined with the face-averaged approach on mixed grids. The method is demonstrated for various inviscid and viscous problems from low to high Mach numbers on two-dimensional mixed grids.

Nishikawa, Hiroaki↗