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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 235 records · Page 13

NBC boil-off calorimeter for measuring thermal conductivity of insulating materials

Modern temperature, pressure and flow sensors along with a high speed digital control system have been incorporated into an existing thermal conductivity apparatus (ASTM C745). The system has also been modified to include the use of liquid helium as the refrigerant, if desired. The apparatus can be used to study thermal conductivity in the temperature range from 4 K to room temperature. Preliminary results on insulating materials indicate that the system update has significantly improved the precision and operational characteristics of the apparatus. Basic principles of operation, sources of system error and the reduction of system error by application of digital control and modern sensors are discussed. Preliminary data are presented.

Dube, W. P.↗

Inversion Reduction Method for Real and Complex Distribution Feeder Models

We report the proliferation of distributed generation on distribution feeders triggers a large number of integration and planning studies. Further, the complexity of distribution feeder models, short simulation time steps, and long simulation horizons rapidly render studies computational burdensome. To mend this issue, we propose a methodology for reducing the number of nodes, loads, generators, line, and transformers of p-phase distribution feeders with unbalanced loads and generation, non-symmetric wire impedance, mutual coupling, shunt capacitance, and changes in voltage and phase. The methodology is derived on a constant power load assumption and employs a Gaussian elimination inversion technique to design the reduced feeder. Compared to previous work by the authors, the inversion reduction takes half the time and voltage errors after reduction are reduced by an order of magnitude. Using a snapshot simulation the reduction is tested on six additional publicly available feeders with a maximum voltage error 0.0075 p.u. regardless of feeder size or complexity, and typical errors on the order of 1 × 10 -4 p.u. Lastly, for a day long quasi-static time series simulation on the UCSD A feeder, errors are shown to increase with changes in loading when a large number of buses removed, but shows less variation for less than 85% of buses removed.

24 POWER TRANSMISSION AND DISTRIBUTION↗

Orbital-optimized MP2.5 and its analytic gradients: Approaching CCSD(T) quality for noncovalent interactions

Orbital-optimized MP2.5 [or simply “optimized MP2.5,” OMP2.5, for short] and its analytic energy gradients are presented. The cost of the presented method is as much as that of coupled-cluster singles and doubles (CCSD) [O(N{sup 6}) scaling] for energy computations. However, for analytic gradient computations the OMP2.5 method is only half as expensive as CCSD because there is no need to solve λ{sub 2}-amplitude equations for OMP2.5. The performance of the OMP2.5 method is compared with that of the standard second-order Møller–Plesset perturbation theory (MP2), MP2.5, CCSD, and coupled-cluster singles and doubles with perturbative triples (CCSD(T)) methods for equilibrium geometries, hydrogen transfer reactions between radicals, and noncovalent interactions. For bond lengths of both closed and open-shell molecules, the OMP2.5 method improves upon MP2.5 and CCSD by 38%–43% and 31%–28%, respectively, with Dunning's cc-pCVQZ basis set. For complete basis set (CBS) predictions of hydrogen transfer reaction energies, the OMP2.5 method exhibits a substantially better performance than MP2.5, providing a mean absolute error of 1.1 kcal mol{sup −1}, which is more than 10 times lower than that of MP2.5 (11.8 kcal mol{sup −1}), and comparing to MP2 (14.6 kcal mol{sup −1}) there is a more than 12-fold reduction in errors. For noncovalent interaction energies (at CBS limits), the OMP2.5 method maintains the very good performance of MP2.5 for closed-shell systems, and for open-shell systems it significantly outperforms MP2.5 and CCSD, and approaches CCSD(T) quality. The MP2.5 errors decrease by a factor of 5 when the optimized orbitals are used for open-shell noncovalent interactions, and comparing to CCSD there is a more than 3-fold reduction in errors. Overall, the present application results indicate that the OMP2.5 method is very promising for open-shell noncovalent interactions and other chemical systems with difficult electronic structures.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

Changes in Liver Volume Observed Following Sorafenib and Liver Radiation Therapy

Purpose: The purpose of this study was to quantify unexpected liver volume reductions in patients treated with sorafenib prior to and during liver radiation therapy (RT). Methods and Materials: Fifteen patients were treated in a phase 1 study of sorafenib for 1 week, followed by concurrent sorafenib-RT (in 6 fractions). Patients had either focal cancer (treated with stereotactic body RT [SBRT]) or diffuse disease (treated with whole-liver RT). Liver volumes were contoured and recorded at planning (day 0) from the exhale CT. After 1 week of sorafenib (day 8), RT image guidance at each fraction was performed using cone beam CT (CBCT). Planning liver contours were propagated and modified on the reconstructed exhale CBCT. This was repeated in 12 patients treated with SBRT alone without sorafenib. Three subsequent patients (2 sorafenib-RT and 1 non-sorafenib) were also assessed with multiphasic helical breath-hold CTs. Results: Liver volume reductions on CBCT were observed in the 15 sorafenib-RT patients (median decrease of 68 cc, P=.02) between day 0 and 8; greater in the focal (P=.025) versus diffuse (P=.52) cancer stratum. Seven patients (47%) had reductions larger than the 95% intraobserver contouring error. Liver reductions were also observed from multiphasic CTs in the 2 additional sorafenib-RT patients between days 0 and 8 (decreases of 232.5 cc and 331.7 cc, respectively) and not in the non-sorafenib patient (increase of 92 cc). There were no significant changes in liver volume between planning and first RT in 12 patients with focal cancer treated with SBRT alone (median increase, 4.8 cc, P=.86). Conclusions: Liver volume reductions were observed after 7 days of sorafenib, prior to RT, most marked in patients with focal liver tumors, suggesting an effect of sorafenib on normal liver. Careful assessment of potential liver volume changes immediately prior to SBRT may be necessary in patients in sorafenib or other targeted therapies.

62 RADIOLOGY AND NUCLEAR MEDICINE↗

Multiple Concurrent Visual-Motor Mappings: Implications for Models of Adaptation

Previous research on adaptation to visual-motor rearrangement suggests that the central nervous system represents accurately only 1 visual-motor mapping at a time. This idea was examined in 3 experiments where subjects tracked a moving target under repeated alternations between 2 initially interfering mappings (the 'normal' mapping characteristic of computer input devices and a 108' rotation of the normal mapping). Alternation between the 2 mappings led to significant reduction in error under the rotated mapping and significant reduction in the adaptation aftereffect ordinarily caused by switching between mappings. Color as a discriminative cue, interference versus decay in adaptation aftereffect, and intermanual transfer were also examined. The results reveal a capacity for multiple concurrent visual-motor mappings, possibly controlled by a parametric process near the motor output stage of processing.

Cunningham, H. A.↗

Reducing systematic error in weak lensing cluster surveys

Weak lensing provides an important route toward collecting samples of clusters of galaxies selected by mass. Subtle systematic errors in image reduction can compromise the power of this technique. We use the B-mode signal to quantify this systematic error and to test methods for reducing this error. We show that two procedures are efficient in suppressing systematic error in the B-mode: (1) refinement of the mosaic CCD warping procedure to conform to absolute celestial coordinates and (2) truncation of the smoothing procedure on a scale of 10'. Application of these procedures reduces the systematic error to 20% of its original amplitude. We provide an analytic expression for the distribution of the highest peaks in noise maps that can be used to estimate the fraction of false peaks in the weak-lensing κ-signal-to-noise ratio (S/N) maps as a function of the detection threshold. Based on this analysis, we select a threshold S/N = 4.56 for identifying an uncontaminated set of weak-lensing peaks in two test fields covering a total area of ∼3 deg{sup 2}. Taken together these fields contain seven peaks above the threshold. Among these, six are probable systems of galaxies and one is a superposition. We confirm the reliability of these peaks with dense redshift surveys, X-ray, and imaging observations. The systematic error reduction procedures we apply are general and can be applied to future large-area weak-lensing surveys. Our high-peak analysis suggests that with an S/N threshold of 4.5, there should be only 2.7 spurious weak-lensing peaks even in an area of 1000 deg{sup 2}, where we expect ∼2000 peaks based on our Subaru fields.

79 ASTRONOMY AND ASTROPHYSICS↗

A General Spatiotemporal Imputation Framework for Missing Sensor Data

Many applications from precision agriculture, environmental monitoring and transportation networks rely on data collected across space and time over a large geographic area. Missing data poses a significant challenge for any data-driven inference and control tasks. Data imputation or the estimation of missing data can help fill these gaps by utilizing inherent spatial relationships and temporal patterns. A variety of spatiotemporal imputation models have been developed to address missing data in spatiotemporal datasets. However, these classical methods rely on the assumption that the underlying data follows a smooth trend and fail to provide accurate estimates when there is a large number of missing points in the data. Even though there are machine learning driven tensor completion approaches such as convolutional neural network based tensor completion (CoSTCo) that capture the non-linear relationships in the dataset, the transductive nature makes the algorithm less scalable. Thus, existing approaches for estimating the missing information do not effectively capture all dimensions of the spatiotemporal data structure, resulting in erroneous predictions and poor performance. The main contributions of this paper are: (1) We propose a novel inductive framework (G-LSTM) for missing data imputation that integrates a graph neural network with LSTMs to effectively capture both spatial and temporal dependencies. (2) Experimental results on a traffic dataset demonstrate that the proposed GNN integrated with an LSTM framework achieves improved imputation and maintains steady performance even when there are extreme missing conditions in comparison with the state-of-the-art imputation framework (i.e, CoSTCo). (3) The simulation results on a traffic network show up to 69% reduction in mean absolute error and 61% reduction in root mean square error when compared to CoSTCo.

Tharzeen, Aabila↗

The behavior of forecast error covariances for a Kalman filter in two dimensions

The behavior of forecast error covariances in a fairly realistic setting is demonstrated via a Kalman filter algorithm. It is used to assimilate simulated data from the existing radiosonde network, from the demonstration network of 31 Doppler wind profilers in the central U.S., and from hypothetical radiometers located at five of the profiler sites. Some theoretical justification of the hypothesis advanced by Phillips (1982), and the hypothesis is used to formulate the model error covariance matrix required by the Kalman filter. The results show that assimilating the profiler wind data leads to a large reduction of forecast/analysis error in heights as well as in winds, over the profiler region and also downstream, when compared with the results of assimilating the radiosonde data alone. The forecast error covariance matrices that the Kalman filter calculates to obtain this error reduction differ considerably from those prescribed by the optimal interpolation schemes that are employed for data assimilation at operational centers.

Cohn, Stephen E.↗

Improving Energy Use Forecast for Campus Micro-grids using Indirect Indicators

The rising global demand for energy is best addressed by adopting and promoting sustainable methods of power consumption. We employ an informatics approach towards forecasting the energy consumption patterns in a university campus micro-grid which can be used for energy use planning and conservation. We use novel indirect indicators of energy that are commonly available to train regression tree models that can predict campus and building energy use for coarse (daily) and fine (15-min) time intervals, utilizing 3 years of sensor data collected at 15min intervals from 170 smart power meters. We analyze the impact of individual features used in the models to identify the ones best suited for the application. Our models show a high degree of accuracy with CV-RMSE errors ranging from 7.45% to 19.32%, and a reduction in error from baseline models by up to 53%.

energy forecast models↗

Workflow Enhancement (WE) Improves Safety in Radiation Oncology: Putting the WE and Team Together

Purpose: To review the impact of a workflow enhancement (WE) team in reducing treatment errors that reach patients within radiation oncology. Methods and Materials: It was determined that flaws in our workflow and processes resulted in errors reaching the patient. The process improvement team (PIT) was developed in 2010 to reduce errors and was later modified in 2012 into the current WE team. Workflow issues and solutions were discussed in PIT and WE team meetings. Due to tensions within PIT that resulted in employee dissatisfaction, there was a 6-month hiatus between the end of PIT and initiation of the renamed/redesigned WE team. In addition to the PIT/WE team forms, the department had separate incident forms to document treatment errors reaching the patient. These incident forms are rapidly reviewed and monitored by our departmental and institutional quality and safety groups, reflecting how seriously these forms are treated. The number of these incident forms was compared before and after instituting the WE team. Results: When PIT was disbanded, a number of errors seemed to occur in succession, requiring reinstitution and redesign of this team, rebranded the WE team. Interestingly, the number of incident forms per patient visits did not change when comparing 6 months during the PIT, 6 months during the hiatus, and the first 6 months after instituting the WE team (P=.85). However, 6 to 12 months after instituting the WE team, the number of incident forms per patient visits decreased (P=.028). After the WE team, employee satisfaction and commitment to quality increased as demonstrated by Gallup surveys, suggesting a correlation to the WE team. Conclusions: A team focused on addressing workflow and improving processes can reduce the number of errors reaching the patient. Time is necessary before a reduction in errors reaching patients will be seen.

62 RADIOLOGY AND NUCLEAR MEDICINE↗

Analyzing the Impact of CryoSat-2 Ice Thickness Initialization on Seasonal Arctic Sea Ice Prediction

Twin 5-month seasonal forecast experiments are performed to predict the September 2018 minimum ice extent using the fully coupled Navy Earth System Prediction Capability (ESPC). In the control run, ensemble forecasts are initialized from the operational US Navy Global Ocean Forecasting System (GOFS) 3.1 for the ocean and sea ice but do not assimilate ice thickness data. Another set of forecasts are initialized from the same GOFS 3.1 fields but with sea ice thickness derived from CryoSat-2 (CS2). The Navy ESPC ensemble mean September 2018 minimum sea ice extent initialized with GOFS 3.1 ice thickness was over-predicted by 0.68 M sq.km (5.27 M sq.km) versus the ensemble set of forecasts initialized with CS2 ice thickness that had an error of 0.40 M sq.km (4.99 M sq.km), a 56% reduction in error. The September mean Integrated Ice Edge Error (IIEE) shows a 19% improvement for the entire Arctic with the CS2 data versus the control run. Comparison against Upward Looking Sonar (ULS) ice thickness in the Beaufort Sea reveals a lower bias and RMSE with the CS2 forecasts at all three moorings. Ice concentration at these locations is also improved, but neither set of experiments show ice free conditions as observed at moorings A and D.

time-lagged ensembles↗

Precipitation Estimation from the ARM Distributed Radar Network during the MC3E Campaign

This study presents radar-based precipitation estimates collected during the two-month DOE ARM - NASA Midlatitude Continental Convective Clouds Experiment (MC3E). Emphasis is on the usefulness of radar observations from the C-band and X-band scanning ARM precipitation radars (CSAPR, XSAPR) for rainfall estimation products to distances within 100 km of the Oklahoma SGP facility. A dense collection of collocated ARM, NASA GPM and nearby surface Oklahoma Mesonet gauge records are consulted to evaluate potential ARM radar-based hourly rainfall products and campaign optimized methods over individual gauge and areal characterizations. Rainfall products are evaluated against the performance of the regional operational NWS NEXRAD S-band radar polarimetric product. Results indicate that the ARM C-band system may achieve similar point and areal-gauge bias and root mean square (rms) error performance to the NEXRAD standard for the variety of MC3E deep convective events sampled when capitalizing on differential phase measurements. The best campaign rainfall performance was achieved when applying radar relations capitalizing on estimates of the specific attenuation from the CSAPR system. The ARM X-band systems only demonstrate solid capabilities as compared to NEXRAD standards for hourly point and areal rainfall accumulations under 10 mm. Here, all methods exhibit a factor of 1.5 to 2.5 reduction in rms errors for areal accumulations over a 15 km2 NASA dense network housing 16 sites having collocated bucket gauges, with the higher error reductions best associated with polarimetric methods.

54 ENVIRONMENTAL SCIENCES↗

Wind tunnel seeding particles for laser velocimeter

The design of an optimal air foil has been a major challenge for aerospace industries. The main objective is to reduce the drag force while increasing the lift force in various environmental air conditions. Experimental verification of theoretical and computational results is a crucial part of the analysis because of errors buried in the solutions, due to the assumptions made in theoretical work. Experimental studies are an integral part of a good design procedure; however, empirical data are not always error free due to environmental obstacles or poor execution, etc. The reduction of errors in empirical data is a major challenge in wind tunnel testing. One of the recent advances of particular interest is the use of a non-intrusive measurement technique known as laser velocimetry (LV) which allows for obtaining quantitative flow data without introducing flow disturbing probes. The laser velocimeter technique is based on measurement of scattered light by the particles present in the flow but not the velocity of the flow. Therefore, for an accurate flow velocity measurement with laser velocimeters, two criterion are investigated: (1) how well the particles track the local flow field, and (2) the requirement of light scattering efficiency to obtain signals with the LV. In order to demonstrate the concept of predicting the flow velocity by velocity measurement of particle seeding, the theoretical velocity of the gas flow is computed and compared with experimentally obtained velocity of particle seeding.

Ghorieshi, Anthony↗

Evaluating GXS Impact in the Context of International Coordination

The proposed NOAA/NASA Geostationary eXtended Observations (GeoXO) program plans to include a hyperspectral infrared (IR) sounder on its central satellite. Expected to launch in the mid-2030s, the GeoXO Sounder (GXS) will join international counterparts in a geostationary orbit. Ahead of launch, the NASA Global Modeling and Assimilation Office (GMAO) assessed the potential effectiveness of GXS both as a single GEO IR sounder and as part of a global ring of such instruments, including those already being built by international agencies. Using an observing system simulation experiment (OSSE) framework, GXS was assessed from a global numerical weather prediction (NWP) perspective. The ability of GXS, both alone and as part of a global ring of GEO sounders, to improve weather prediction of thermodynamic variables was evaluated globally and regionally. Compared to a control, GXS dominated regional analysis and forecast improvements, and contributed significantly to global increases in forecast skill. However, more sustained global improvements on the order of 4 days rely on international partnerships. Using the FSOI metric over CONUS, the GXS observations provide the strongest radiance impact on the moist energy error norm reduction. Additionally, GXS shows the capability to improve hurricane forecast track errors, resulting in improved forecast warnings. Overall, the persistent atmospheric profile information from GXS over much of the western hemisphere provide an opportunity to improve the representation of weather systems and their forecasts.

Erica McGrath-Spangler↗

Evaluating the Impact of Geostationary Sounders in the Context of International Coordination

The proposed NOAA/NASA Geostationary eXtended Observations (GeoXO) program plans to include a hyperspectral infrared (IR) sounder (GXS) on its central satellite, joining international counterparts. Ahead of launch, the NASA Global Modeling and Assimilation Office (GMAO) assessed the potential effectiveness of GXS both as a lone sounder in a GEO orbit and as part of a global ring of such instruments. Using an observing system simulation experiment (OSSE) framework from a global numerical weather prediction (NWP) perspective, the ability of GXS and the global ring to improve weather prediction of thermodynamic variables was assessed both globally and regionally. GXS dominated regional analysis and forecast improvements and contributed significantly to global increases in forecast skill. However, more sustained global improvements on the order of 4 days rely on international partnerships. Over CONUS, the FSOI metric showed the GXS observations provide the strongest radiance impact on the moist energy error norm reduction. Additionally, GXS shows the capability to improve hurricane forecast track errors, resulting in improved forecast warnings. Overall, the persistent atmospheric profile information from GXS over much of the western hemisphere provide an opportunity to improve the representation of weather systems and their forecasts.

Erica L. McGrath-Spangler↗

Evaluating the Impact of Geostationary Sounders in the Context of International Coordination

The proposed NOAA/NASA Geostationary eXtended Observations (GeoXO) program plans to include a hyperspectral infrared (IR) sounder (GXS) on its central satellite, joining international counterparts. Ahead of launch, the NASA Global Modeling and Assimilation Office (GMAO) assessed the potential effectiveness of GXS both as a lone sounder in a GEO orbit and as part of a global ring of such instruments. Using an observing system simulation experiment (OSSE) framework from a global numerical weather prediction (NWP) perspective, the ability of GXS and the global ring to improve weather prediction of thermodynamic variables was assessed both globally and regionally. GXS dominated regional analysis and forecast improvements and contributed significantly to global increases in forecast skill. However, more sustained global improvements on the order of 4 days rely on international partnerships. Over CONUS, the FSOI metric showed the GXS observations provide the strongest radiance impact on the moist energy error norm reduction. Additionally, GXS shows the capability to improve hurricane forecast track errors, resulting in improved forecast warnings. Overall, the persistent atmospheric profile information from GXS over much of the western hemisphere provide an opportunity to improve the representation of weather systems and their forecasts.

Erica McGrath-Spangler↗

Evaluating GXS Impact in the Context of International Coordination

The proposed NOAA/NASA Geostationary eXtended Observations (GeoXO) program plans to include a hyperspectral infrared (IR) sounder on its central satellite. Expected to launch in the mid-2030s, the GeoXO Sounder (GXS) will join international counterparts in a geostationary orbit. Ahead of launch, the NASA Global Modeling and Assimilation Office (GMAO) assessed the potential effectiveness of GXS both as a single GEO IR sounder and as part of a global ring of such instruments, including those already being built by international agencies. Using an observing system simulation experiment (OSSE) framework, GXS was assessed from a global numerical weather prediction (NWP) perspective. The ability of GXS, both alone and as part of a global ring of GEO sounders, to improve weather prediction of thermodynamic variables was evaluated globally and regionally. Compared to a control, GXS dominated regional analysis and forecast improvements, and contributed significantly to global increases in forecast skill. However, more sustained global improvements on the order of 4 days rely on international partnerships. Using the FSOI metric over CONUS, the GXS observations provide the strongest radiance impact on the moist energy error norm reduction. Additionally, GXS shows the capability to improve hurricane forecast track errors, resulting in improved forecast warnings. Overall, the persistent atmospheric profile information from GXS over much of the western hemisphere provide an opportunity to improve the representation of weather systems and their forecasts.

Erica McGrath-Spangler↗

Analyzing the Effects of Geometric Lane Constraints on Radar-Based Sensing of Available Vehicle Headway Using Mapped Lane Geometry and Camera Registration of Lane Position

Commercial trucks are currently equipped with a single front-facing RADAR mounted on the front bumper, as this is a sensor useful for Cooperative Adaptive Cruise Control, Emergency Braking Systems, and many similar Connected and Automated vehicle functions that require longitudinal vehicle control. This paper investigates the use of a bumper-mounted RADAR to perform traffic characterization around the ego-vehicle to obtain an estimate of the furthest headway that can be considered as a reliable estimate of open maneuvering space, such that there are no vehicles within the same lane as the ego-vehicle. This available headway in front of a vehicle is an important parameter in an ongoing study whose goal is to obtain improvements in fuel economy for highway driving of a tractor-trailer. But headway availability depends on the correct attribution of RADAR measured vehicles to be either within the ego-lane, or outside the lane. The attribution of lane designations to specific RADAR targets depend strongly on lane geometry and the ability to align RADAR measurements to the ego-lane. This work investigates how knowledge of lane geometries, as well as sensor performance characteristics, may improve the trust in a RADAR measurement of open headway distance in front of a vehicle. Specifically, several strategies for associating local traffic either within or excluded from the ego lane are considered, and the possible sources of error in headway calculations are investigated for each strategy. The strategies differ by the availability of lane geometry information and RADAR target association to lane constraints, which in turn is assumed to be supplied by the use of map data and secondary camera measurements. It is observed that combining RADAR with lane-geometry maps help detect headway up to and beyond RADAR range limit with exceptions tied to a particular road. These errors can further be minimized by using camera measurements, and this reduction in error is analyzed assuming errors associated with registering images to lane markers. Here, the results, based on actual highway routes measured with our test vehicle, reveal: that RADAR data without lane geometry strongly limits the trusted headway measurement from this sensor; that lane geometry maps can greatly increase the trusted range, usually beyond the RADAR’s range limits; and that image-based registration of lane markers to lane geometry should have accuracies allowing full-range trust in the RADAR target measurements of headway.

33 ADVANCED PROPULSION SYSTEMS↗