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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 541 records · Page 30

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DOE OSTI2021

Intermediate scattering functions of a rigid body monoclonal antibody protein in solution studied by dissipative particle dynamic simulation

In the past decade, there was increased research interest in studying internal motions of flexible proteins in solution using Neutron Spin Echo (NSE) as NSE can simultaneously probe the dynamics at the length and time scales comparable to protein domain motions. However, the collective intermediate scattering function (ISF) measured by NSE has the contributions from translational, rotational, and internal motions, which are rather complicated to be separated. Widely used NSE theories to interpret experimental data usually assume that the translational and rotational motions of a rigid particle are decoupled and independent to each other. To evaluate the accuracy of this approximation for monoclonal antibody (mAb) proteins in solution, dissipative particle dynamic computer simulation is used here to simulate a rigid-body mAb for up to about 200 ns. The total ISF together with the ISFs due to only the translational and rotational motions as well as their corresponding effective diffusion coefficients is calculated. The aforementioned approximation introduces appreciable errors to the calculated effective diffusion coefficients and the ISFs. For the effective diffusion coefficient, the error introduced by this approximation can be as large as about 10% even though the overall agreement is considered reasonable. Thus, we need to be cautious when interpreting the data with a small signal change. In addition, the accuracy of the calculated ISFs due to the finite computer simulation time is also discussed.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗

DOE OSTI2020

Traffic Prediction for Merging Coordination Control in Mixed Traffic Scenarios

Connected and autonomous vehicles (CAVs) have the potential to bring in safety, mobility, and energy benefits to transportation. The control decisions of CAVs are usually determined for a look-ahead horizon based on previewed traffic information. This requires an effective prediction of future traffic conditions and its integration with the CAV control framework. However, the short-term traffic prediction using information from connectivity is a challenging research topic, especially for mixed traffic scenarios. This work focuses on the development of a traffic prediction framework for a merging coordination controller. The previously developed merging controller coordinates the merging sequence and travel speed of CAVs to maximize the energy efficiency and overall mobility. In mixed traffic scenarios, the controller receives information regarding the position of all the vehicles traveling inside a control zone and controls the desired speed of all CAVs. The controller has no control on the human-driven vehicles. The merging controller does not have direct information or an explicit prediction on the behaviors of human-driven vehicles. Aiming to improve the performance of the merging controller in various mixed traffic conditions, a traffic prediction algorithm is developed and evaluated in this work. The performance of this traffic prediction algorithm is investigated for various penetration rates of connectivity for a single-lane secondary road merging to a single-lane primary road. The results show that compared to a constant speed assumption of human-driven vehicles, the proposed traffic prediction algorithm is able to reduce the prediction error of the arrival time of human-driven vehicles at the merging zone by more than 50%.

Shao, Yunli↗

DOE OSTI2022

High-fidelity retrieval from instantaneous line-of-sight returns of nacelle-mounted lidar including supervised machine learning

Abstract. Wind turbine applications that leverage nacelle-mounted Doppler lidar are hampered by several sources of uncertainty in the lidar measurement, affecting both bias and random errors. Two problems encountered especially for nacelle-mounted lidar are solid interference due to intersection of the line of sight with solid objects behind, within, or in front of the measurement volume and spectral noise due primarily to limited photon capture. These two uncertainties, especially that due to solid interference, can be reduced with high-fidelity retrieval techniques (i.e., including both quality assurance/quality control and subsequent parameter estimation). Our work compares three such techniques, including conventional thresholding, advanced filtering, and a novel application of supervised machine learning with ensemble neural networks, based on their ability to reduce uncertainty introduced by the two observed nonideal spectral features while keeping data availability high. The approach leverages data from a field experiment involving a continuous-wave (CW) SpinnerLidar from the Technical University of Denmark (DTU) that provided scans of a wide range of flows both unwaked and waked by a field turbine. Independent measurements from an adjacent meteorological tower within the sampling volume permit experimental validation of the instantaneous velocity uncertainty remaining after retrieval that stems from solid interference and strong spectral noise, which is a validation that has not been performed previously. All three methods perform similarly for non-interfered returns, but the advanced filtering and machine learning techniques perform better when solid interference is present, which allows them to produce overall standard deviations of error between 0.2 and 0.3 m s−1, or a 1 %–22 % improvement versus the conventional thresholding technique, over the rotor height for the unwaked cases. Between the two improved techniques, the advanced filtering produces 3.5 % higher overall data availability, while the machine learning offers a faster runtime (i.e., ∼ 1 s to evaluate) that is therefore more commensurate with the requirements of real-time turbine control. The retrieval techniques are described in terms of application to CW lidar, though they are also relevant to pulsed lidar. Previous work by the authors (Brown and Herges, 2020) explored a novel attempt to quantify uncertainty in the output of a high-fidelity lidar retrieval technique using simulated lidar returns; this article provides true uncertainty quantification versus independent measurement and does so for three techniques rather than one.

47 OTHER INSTRUMENTATION↗

NASA NTRS1976

Models and error analyses in urban air quality estimation

Estimation theory has been applied to a wide range of aerospace problems. Application of this expertise outside the aerospace field has been extremely limited, however. This paper describes the use of covariance error analysis techniques in evaluating the accuracy of pollution estimates obtained from a variety of concentration measuring devices. It is shown how existing software developed for aerospace applications can be applied to the estimation of pollution through the processing of measurement types involving a range of spatial and temporal responses. The modeling of pollutant concentration by meandering Gaussian plumes is described in some detail. Time averaged measurements are associated with a model of the average plume, using some of the same state parameters and thus avoiding the problem of state memory. The covariance analysis has been implemented using existing batch estimation software. This usually involves problems in handling dynamic noise; however, the white dynamic noise has been replaced by a band-limited process which can be easily accommodated by the software.

Englar, T., Jr.↗

NASA NTRS1987

Model-based analysis of control/display interaction in the hover task

The effect of Control/Display interaction in the hover task is analyzed using an optimal control approach to modeling pilot control behavior. The control/display configurations considered are those previously evaluated in a flight research program. The experimental data-base is reviewed and the procedure for modeling the task and the displayed information is presented in detail. All model-based results, time-domain as well as frequency-domain, are found to correlate extremely well with the subjective pilot ratings and comments. Time-domain measures consist of root mean-square errors and control inputs, attention allocation to displayed quantities, and magnitudes of task objective function. Frequency-domain measures include bandwidth, stability margins, and pilot phase compensation. Results are also shown to agree with previous findings on task interference in multi-axis tasks.

Schmidt, David K.↗

NASA NTRS1989

The effects of atmospheric turbulence on precision optical measurements used for antenna-pointing compensation

Blind pointing of the Deep Space Network (DSN) 70-meter antennas can be improved if distortions of the antenna structure caused by unpredictable environmental loads can be measured in real-time, and the resulting boresight shifts evaluated and incorporated into the pointing control loops. The measurement configuration of a proposed pointing compensation system includes an optical range sensor that measures distances to selected points on the antenna surface. The effect of atmospheric turbulence on the accuracy of optical distance measurements and a method to make in-situ determinations of turbulence-induced measurement errors are discussed.

Nerheim, N.↗

NASA NTRS2017

A 30+ Year AVHRR Land Surface Reflectance Climate Data Record and Its Application to Wheat Yield Monitoring

The Advanced Very High Resolution Radiometer (AVHRR) sensor provides a unique global remote sensing dataset that ranges from the 1980's to the present. Over the years, several efforts have been made on the calibration of the different instruments to establish a consistent land surface reflectance time-series and to augment the AVHRR data record with data from other sensors such as the Moderate Resolution Imaging Spectroradiometer (MODIS). In this paper, we present a summary of all the corrections applied to the AVHRR Surface Reflectance and NDVI Version 4 Product, developed in the framework of the National Oceanic and Atmospheric Administration (NOAA) Climate Data Record (CDR) program. These corrections result from assessment of the geo-location, improvement of the cloud masking and calibration monitoring. Additionally, we evaluate the performance of the surface reflectance over the AERONET sites by a cross-comparison with MODIS, which is an already validated product, and evaluation of a downstream Leaf Area Index (LAI) product. We demonstrate the utility of this long time-series by estimating the winter wheat yield over the USA. The methods developed by [1] and [2] are applied to both the MODIS and AVHRR data. Comparison of the results from both sensors during the MODIS-era shows the consistency of the dataset with similar errors of 10%. When applying the methods to AVHRR historical data from the 1980's, the results have errors equivalent to those derived from MODIS.

AVHRR↗

NASA NTRS2019

Common Habitat for Long Duration Transit and Surface Operations

This concept is based on the Skylab II concept, which proposes using a SLS propellant tank as the primary structure of a habitat. Common Habitat takes this a step further, proposing an interior architecture that is equally viable as a lunar surface hab, transit hab, and Mars surface hab, thus enabling a single development to support all three long duration habitat roles. Common Habitat has been pursued by the PI and co-investigators at MSFC and other centers in a spare time / funding available basis, often with heavy student intern support. Student resources have developed preliminary concepts, but these models must be refined to reflect accurate vehicle subsystems, utilities, stowage, workstations, and other crew systems. This investigation applies NASA civil servant and contractor expertise to correct errors in the most recent student concepts in order to prepare them for future human-in-the-loop evaluations to determine the most viable configuration for a Common Habitat. In prior studies there was never an opportunity to trade both crew size and internal orientation. Prior work has been a series of point designs with inconsistent design constraints, making apples to apples comparisons impossible. The most recent student work produced CAD models of four habitat variants for future use in a trade study, but the student products contain model construction and geometry errors, inaccurate subsystems design and placement, and unrealistic structural elements and outfitting. These must be corrected before the models can be moved into a VR environment for humanin- the-loop testing. Through consultation with SMEs throughout the Agency, the fidelity of these designs will be upgraded to a level of quality sufficient to make a comparative analysis of crew size sensitivity and internal orientation. The product of this activity is four upgraded CAD models, each reflecting a different configuration of the Common Habitat. One is a horizontal configuration using the full length of the SLS LOX tank. One is a vertical configuration using the same tank dimensions. The third is a horizontal configuration using a truncated SLS LOX tank (half the barrel length). The fourth is a vertical configuration of the half-length SLS LOX tank.

Howard, Robert L.↗

NASA NTRS2019

Common Habitat for Long Duration Transit and Surface Operations

Howard, Robert L.↗

DOE OSTI2023

Preservation of kinetics parameters generated by Monte Carlo calculations in two-step deterministic calculations

The generation of accurate kinetic parameters such as mean generation time Λ and effective delayed neutron fraction β eff via Monte Carlo codes is established. Employing these in downstream deterministic codes warrants another step to ensure no additional error is introduced by the low-order transport operator when computing forward and adjoint fluxes for bilinear weighting of these parameters. Another complexity stems from applying superhomogenization (SPH) equivalence in non-fundamental mode approximations, where reference and low-order calculations rely on a 3D full core model. In these cases, SPH factors can optionally be computed for only part of the geometry while preserving reaction rates and K-effective, but the impact of such approximations on kinetics parameters has not been thoroughly studied. This paper aims at studying the preservation of bilinearly-weighted quantities in the Serpent–Griffin calculation procedure. Diffusion and transport evaluations of IPEN/MB-01, Godiva, and Flattop were carried out with the Griffin reactor physics code, testing available modeling options using Serpent-generated multigroup cross sections and equivalence data. Verifying Griffin against Serpent indicates sensitivities to multigroup energy grid selection and regional application of SPH equivalence, introducing significant errors; these were demonstrated to be reduced through the use of a transport method together with a finer energy grid.

22 GENERAL STUDIES OF NUCLEAR REACTORS↗

DOE OSTI2023

Genetic algorithm optimization of a chemical kinetic mechanism for propane at engine relevant conditions

Propane has demonstrated significant potential for reductions in greenhouse gas and pollutant emissions in medium- and heavy-duty engine applications, but further improvements require accurate, compact, and scalable chemical kinetic mechanisms to design the next generation of propane fueled engines, particularly at the boosted operating conditions necessary to meet the power density demand of medium- and heavy-duty applications. In this work, six key chemical reactions were identified in a reduced mechanism with 70 species and 352 reactions through a sensitivity analysis performed at conditions typical of thermodynamic trajectories observed in a high compression ratio, long stroke engine operated on propane from throttled to boosted operating conditions. While the original mechanism was validated against rapid compression machine (RCM) data, it was found to overpredict experimental autoignition tendencies in 2-zone, 0-D SI engine simulations performed in Chemkin Pro. Subsequently, a genetic algorithm approach was used to optimize the six reaction rate parameters within established uncertainty bounds by performing RCM simulations and comparing to two independent sets of literature ignition delay times for propane, thus generating two new kinetic mechanisms. The first optimization achieved a mean absolute percent error (MPE) reduction in 2nd stage ignition delay of 61.4% in seven generations, while the second optimization utilized a newer experimental RCM dataset, and achieved MPE reduction of 56.7% in seven generations, and further marginal improvement to 57.8% reduction in 34 generations. Finally, the two mechanisms were then evaluated again in the 2-zone 0-D SI engine model in Chemkin Pro comparing typical mean and knocking cycle trajectories, and it was found that the second optimized mechanism provided better prediction of knock onset at the representative conditions evaluated in this work, particularly for higher load operating conditions.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

DOE OSTI2026

AutoLabs: cognitive multi-agent systems with self-correction for autonomous chemical experimentation

The automation of chemical research through self-driving laboratories (SDLs) promises to accelerate scientific discovery, yet the reliability and granular performance of the underlying AI agents remain critical, under-examined challenges. In this work, we introduce AutoLabs, a self-correcting, multi-agent architecture designed to autonomously translate natural-language instructions into executable protocols for a high-throughput liquid handler. The system engages users in dialogue, decomposes experimental goals into discrete tasks for specialized agents, performs tool-assisted stoichiometric calculations, and iteratively self-corrects its output before generating a hardware-ready file. We present a comprehensive evaluation framework featuring five benchmark experiments of increasing complexity, from simple sample preparation to multi-plate timed syntheses. Through a systematic ablation study of 20 agent configurations, we assess the impact of reasoning capacity, architectural design (single- vs. multi-agent), tool use, and self-correction mechanisms. Our results demonstrate that agent reasoning capacity is the most critical factor for success, reducing quantitative errors in chemical amounts (nRMSE) by over 85% in complex tasks. When combined with a multi-agent architecture and iterative self-correction, AutoLabs approaches expert-authored reference procedures on the benchmark (F1-score > 0.89) on challenging multi-plate syntheses. These findings establish a clear blueprint for developing robust and trustworthy AI partners for autonomous laboratories, highlighting the synergistic effects of modular design, advanced reasoning, and self-correction to ensure both performance and reliability in high-stakes scientific applications. Code: https://github.com/pnnl/autolabs

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

DOE OSTI2020

Non-autoregressive time-series methods for stable parametric reduced-order models

Advection-dominated dynamical systems, characterized by partial differential equations, are found in applications ranging from weather forecasting to engineering design where accuracy and robustness are crucial. There has been significant interest in the use of techniques borrowed from machine learning to reduce the computational expense and/or improve the accuracy of predictions for these systems. These rely on the identification of a basis that reduces the dimensionality of the problem and the subsequent use of time series and sequential learning methods to forecast the evolution of the reduced state. Often, however, machine-learned predictions after reduced-basis projection are plagued by issues of stability stemming from incomplete capture of multiscale processes as well as due to error growth for long forecast durations. To address these issues, we have developed a non-autoregressive time series approach for predicting linear reduced-basis time histories of forward models. In particular, we demonstrate that non-autoregressive counterparts of sequential learning methods such as long short-term memory (LSTM) considerably improve the stability of machine-learned reduced-order models. Further, we evaluate our approach on the inviscid shallow water equations and show that a non-autoregressive variant of the standard LSTM approach that is bidirectional in the principal component directions obtains the best accuracy for recreating the nonlinear dynamics of partial observations. Moreover-and critical for many applications of these surrogates-inference times are reduced by three orders of magnitude using our approach, compared with both the equation-based Galerkin projection method and the standard LSTM approach.

97 MATHEMATICS AND COMPUTING↗

DOE OSTI2024

Optimization of prefabricated component installation using a real-time evaluator (RTE) connection locating system

Prefabrication promises to industrialize the construction industry. By constructing elements within a manufacturing environment, producers can better control quality and maximize production efficiency. Since the major adoption of prefabrication, a wide variety of prefabricated components have been produced for varying applications such as new construction and exterior wall retrofits. While the production processes of these prefabricated components have seen much innovation, the installation process has remained relatively unchanged for decades. To innovate the installation process with modern technologies, a real-time evaluator (RTE) has been developed to reduce the installation cost of prefabricated components by reducing installation time, decreasing rework, and improving accuracy. The RTE uses developed software solutions with off-the-shelf hardware to assist erectors in completing an installation by measuring the real-time positions of connections and prefabricated components, providing installation guidance through a graphical user interface, and monitoring the accumulated installation errors. An overview of the RTE and proposed workflow is presented. A connection locating system that guides users in expediting the installation of connections is introduced. Laboratory experiments were conducted to determine the accuracy improvement and time savings of the RTE in installing connections for prefabricated components. RTE enabled a time saving of up to 37% compared to traditional connection installation methods using handheld measurement tools.

Hayes, Nolan↗

NASA NTRS1971

Tracer techniques for urine volume determination and urine collection and sampling back-up system

The feasibility, functionality, and overall accuracy of the use of lithium were investigated as a chemical tracer in urine for providing a means of indirect determination of total urine volume by the atomic absorption spectrophotometry method. Experiments were conducted to investigate the parameters of instrumentation, tracer concentration, mixing times, and methods for incorporating the tracer material in the urine collection bag, and to refine and optimize the urine tracer technique to comply with the Skylab scheme and operational parameters of + or - 2% of volume error and + or - 1% accuracy of amount of tracer added to each container. In addition, a back-up method for urine collection and sampling system was developed and evaluated. This back-up method incorporates the tracer technique for volume determination in event of failure of the primary urine collection and preservation system. One chemical preservative was selected and evaluated as a contingency chemical preservative for the storage of urine in event of failure of the urine cooling system.

Ramirez, R. V.↗

NASA NTRS1973

SUMC/MPOS/HAL interface study

The implementation of the HAL/S language on the IBM-360, and in particular the mechanization of its real time, I/O, and error control statements within the OS-360 environment is described. The objectives are twofold: (1) An analysis and general description of HAL/S real time, I/O, and error control statements and the structure required to mechanize these statements. The emphasis is on describing the logical functions performed upon execution of each HAL statement rather than defining whether it is accomplished by the compiler or operating system. (2) An identification of the OS-360 facilities required during execution of HAL/S code as implemented for the current HAL/S-360 compiler; and an evaluation of the aspects involved with interfacing HAL/S with the SUMC operating system utilizing either the HAL/S-360 compiler or by designing a new HAL/S-SUMC compiler.

Saponaro, J. A.↗

NASA NTRS1973

Evaluation of Raman scattering as a sensor of temperature and molecular density

The performance of the Raman scattering technique for the remote monitoring of temperature and molecular number density in various wind tunnel and engine testing facilities has been experimentally evaluated. Temperature measurements were made by monitoring the pure rotational spectrum of nitrogen and the rotational branch separations of nu2 of CF4 for temperatures in the range 300 to 1000 K. These measurements yielded an average error of 2.6 and 7.6%, respectively, for temperature measurements at pressures near 1 atm. Molecular number density measurements with 20% error could be made at densities as low as 3.5 times 10 to the 22-nd power per cu m by monitoring the 6 to 8 rotational transition of nitrogen, 3.5 times 10 to the 23-rd power per cu m by monitoring the Q-branch of the fundamental vibrational transition of nitrogen, and 7 times 10 to the 22-nd power per cu m by monitoring the nu1 fundamental vibrational transition of CF4.

Bandy, A. R.↗

NASA NTRS1981

Area estimation of forestlands in southwestern Michigan from LANDSAT imagery

The accuracy of mapping and estimating the area of forestlands in southwestern Michigan from winter and fall LANDSAT images was evaluated. All omission and commission errors in the LANDSAT forest maps were identified and mapped through comparison with an existing detailed forest cover type map. Accuracies ranged from 74.0% to 98.5% and were higher for the winter imagery. Most errors (85%) occurred along the perimeter of forestlands and were less than 4 hectares (10 acres) and size. Other factors affecting interpretation are reported as well as time and image availability considerations.

Karteris, M. A.↗